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Stefan Schmid

Stefan Schmid appears in the imported research catalog. Authorship, coauthor and topic links are available while profile ownership is still unclaimed.

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Networking and Internet ArchitectureDistributed, Parallel, and Cluster ComputingData Structures and AlgorithmsBiological Physicsphysics.med-phQuantitative MethodsCryptography and SecurityComputer Science and Game Theorycond-mat.quant-gasMachine Learningphysics.atom-phphysics.soc-phquant-phSocial and Information NetworksApplicationsArtificial IntelligenceComputational Complexitycs.CYDiscrete MathematicsLogic in Computer Sciencemath.OCMultiagent SystemsPerformancephysics.data-anSoftware EngineeringTissues and Organs

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Published work

78 published item(s)

preprint2026arXiv

A Tutorial on Controlling Metasurfaces from the Network Perspective

Metasurfaces have emerged as transformative electromagnetic structures for wireless communications, enabling the real-time control over wave propagation, yielding potential for improved data rates, privacy, energy efficiency and even precise environmental sensing. This tutorial offers a perspective on controlling metasurfaces by treating them as components of a larger networked system. Towards this end, we first review the physical principles of metasurfaces and their various applications, followed by an exploration of manufacturing approaches for creating these structures. Then, aligning with standard network layer concepts, we describe the modeling of metasurfaces as wave routers, enabling us to describe systems of metasurfaces using graph theory. This approach enables the development of a performance objective framework for optimizing these systems, while classes of heuristic and path-finding-driven algorithms are discussed as practical solvers. The paper also examines the integration of metasurfaces with communication systems, by presenting their overall workflow, discussing its relation to ongoing standardization efforts, as well as defining a context for their integration to network simulators, using Omnet++ as a driving example. Finally, the paper explores future directions for research in this field, identifying graph-theoretic, standardization and integration challenges, relating to several networking disciplines including AI-driven applications.

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preprint2026arXiv

Complexity of Perfect and Ideal Resilience Verification in Fast Re-Route Networks

To achieve fast recovery from link failures, most modern communication networks feature fully decentralized fast re-routing mechanisms. These re-routing mechanisms rely on pre-installed static re-routing rules at the nodes (the routers), which depend only on local failure information, namely on the failed links incident to the node. Ideally, a network is perfectly resilient: the re-routing rules ensure that packets are always successfully routed to their destinations as long as the source and the destination are still physically connected in the underlying network after the failures. Unfortunately, there are examples where achieving perfect resilience is not possible. Surprisingly, only very little is known about the algorithmic aspect of when and how perfect resilience can be achieved. We investigate the computational complexity of analyzing such local fast re-routing mechanisms. Our main result is a negative one: we show that even checking whether a given set of static re-routing rules ensures perfect resilience is coNP-complete. We also show coNP-completeness of the so-called ideal resilience, a weaker notion of resilience often considered in the literature. Additionally, we investigate other fundamental variations of the problem. In particular, we show that our coNP-completeness proof also applies to scenarios where the re-routing rules have specific patterns (known as skipping in the literature). On the positive side, for scenarios where nodes do not have information about the link from which a packet arrived (the so-called in-port), we present linear-time algorithms for both the verification and synthesis problem for perfect resilience.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Practical Validity Conditions for Byzantine-Tolerant Federated Learning

Robust aggregation is the core operation in Byzantine-tolerant federated learning. To ensure the quality of aggregation independently of data distribution or attacks, validity conditions are needed. They provide geometric guarantees of where the output of the aggregation must lie. The widespread convex validity requires the output to lie in the convex hull of the honest vectors. Although this guarantee is strong in theory, it is poorly suited to modern federated learning systems, as it has dimension-dependent resilience and excludes many practical aggregation rules. We introduce the minimum enclosing ball (MEB) validity condition for robust aggregation, as well as its multiplicative relaxation, $c$-MEB validity, where $c$ is a constant. We show that exact MEB validity still suffers from limited resilience, while relaxed $c$-MEB validity is achievable if a majority of clients is honest, i.e. $n>2t$. We give an optimal MinMax-MEB rule for the relaxed condition with the bound $c<\sqrt{2}$ and prove explicit relaxed-MEB guarantees for standard aggregators including minimum-diameter averaging, medoid and geometric median. Finally, we relate MEB validity to convex, relaxed-convex and box validity studied in prior literature, thus providing a systematic map of geometric validity conditions for Byzantine-robust aggregation. Our results show that relaxed MEB validity connects validity conditions in distributed computing and Byzantine-tolerant aggregation rules, and offers a practical alternative to convex validity.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Resilient Byzantine Agreement with Predictions

This paper studies the Byzantine Agreement problem where the nodes have access to a predictor that flags nodes for suspicion of faulty (Byzantine) behavior. We focus on algorithmic resilience -- the maximum number of faulty nodes an algorithm can tolerate -- and present algorithms and impossibility results whose resilience depend on the accuracy of the predictor. As our first main result, we bring a complete characterization of the consistency--robustness trade-offs in both the non-authenticated and authenticated settings: for $n$ nodes and a parameter $α\in [0, 1]$, we present algorithms that tolerate up to $α\cdot n$ faulty nodes when the predictor is correct (consistency), and up to $\frac{1-α}{2} \cdot n - 1$ faulty nodes when the predictor is arbitrarily wrong (robustness); in the authenticated setting the robustness bound improves to $(1-α) \cdot n - 1$. These trade-offs are exactly tight as we show that one additional faulty node renders the problem impossible. Our second main result characterizes smoothness: the rate at which resilience degrades as the predictor becomes less accurate. We show that resilience linearly decreases in the number of wrong predictions as long as that number stays within a constant fraction of $n$. Concretely, in the non-authenticated setting each additional wrong prediction loses one unit of resilience, whereas in the authenticated setting the decline is halved since two wrong predictions are needed to lose one unit of resilience.

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preprint2026arXiv

TAPAAL HyperLTL: A Tool for Checking Hyperproperties of Petri Nets

Petri nets are a modeling formalism capable of describing complex distributed systems and there exists a large number of both academic and industrial tools that enable automatic verification of model properties. Typical questions include reachability analysis and model checking against logics like LTL and CTL. However, these logics fall short when describing properties like non-interference and observational determinism that require simultaneous reasoning about multiple traces of the model and can thus only be expressed as hyperproperties. We introduce, to the best of our knowledge, the first HyperLTL model checker for Petri nets. The tool is fully integrated into the verification framework TAPAAL and we describe the semantics of the hyperlogic, present the tool's architecture and GUI, and evaluate the performance of the HyperLTL verification engine on two benchmarks of problems originating from the computer networking domain.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

Credence: Augmenting Datacenter Switch Buffer Sharing with ML Predictions

Packet buffers in datacenter switches are shared across all the switch ports in order to improve the overall throughput. The trend of shrinking buffer sizes in datacenter switches makes buffer sharing extremely challenging and a critical performance issue. Literature suggests that push-out buffer sharing algorithms have significantly better performance guarantees compared to drop-tail algorithms. Unfortunately, switches are unable to benefit from these algorithms due to lack of support for push-out operations in hardware. Our key observation is that drop-tail buffers can emulate push-out buffers if the future packet arrivals are known ahead of time. This suggests that augmenting drop-tail algorithms with predictions about the future arrivals has the potential to significantly improve performance. This paper is the first research attempt in this direction. We propose Credence, a drop-tail buffer sharing algorithm augmented with machine-learned predictions. Credence can unlock the performance only attainable by push-out algorithms so far. Its performance hinges on the accuracy of predictions. Specifically, Credence achieves near-optimal performance of the best known push-out algorithm LQD (Longest Queue Drop) with perfect predictions, but gracefully degrades to the performance of the simplest drop-tail algorithm Complete Sharing when the prediction error gets arbitrarily worse. Our evaluations show that Credence improves throughput by $1.5$x compared to traditional approaches. In terms of flow completion times, we show that Credence improves upon the state-of-the-art approaches by up to $95\%$ using off-the-shelf machine learning techniques that are also practical in today's hardware. We believe this work opens several interesting future work opportunities both in systems and theory that we discuss at the end of this paper.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Dynamic Maintenance of Monotone Dynamic Programs and Applications

Dynamic programming (DP) is one of the fundamental paradigms in algorithm design. However, many DP algorithms have to fill in large DP tables, represented by two-dimensional arrays, which causes at least quadratic running times and space usages. This has led to the development of improved algorithms for special cases when the DPs satisfy additional properties like, e.g., the Monge property or total monotonicity. In this paper, we consider a new condition which assumes (among some other technical assumptions) that the rows of the DP table are monotone. Under this assumption, we introduce a novel data structure for computing $(1+\varepsilon)$-approximate DP solutions in near-linear time and space in the static setting, and with polylogarithmic update times when the DP entries change dynamically. To the best of our knowledge, our new condition is incomparable to previous conditions and is the first which allows to derive dynamic algorithms based on existing DPs. Instead of using two-dimensional arrays to store the DP tables, we store the rows of the DP tables using monotone piecewise constant functions. This allows us to store length-$n$ DP table rows with entries in $[0,W]$ using only polylog$(n,W)$ bits, and to perform operations, such as $(\min,+)$-convolution or rounding, on these functions in polylogarithmic time. We further present several applications of our data structure. For bicriteria versions of $k$-balanced graph partitioning and simultaneous source location, we obtain the first dynamic algorithms with subpolynomial update times, as well as the first static algorithms using only near-linear time and space. Additionally, we obtain the currently fastest algorithm for fully dynamic knapsack.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

SeedTree: A Dynamically Optimal and Local Self-Adjusting Tree

We consider the fundamental problem of designing a self-adjusting tree, which efficiently and locally adapts itself towards the demand it serves (namely accesses to the items stored by the tree nodes), striking a balance between the benefits of such adjustments (enabling faster access) and their costs (reconfigurations). This problem finds applications, among others, in the context of emerging demand-aware and reconfigurable datacenter networks and features connections to self-adjusting data structures. Our main contribution is SeedTree, a dynamically optimal self-adjusting tree which supports local (i.e., greedy) routing, which is particularly attractive under highly dynamic demands. SeedTree relies on an innovative approach which defines a set of unique paths based on randomized item addresses, and uses a small constant number of items per node. We complement our analytical results by showing the benefits of SeedTree empirically, evaluating it on various synthetic and real-world communication traces.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

A Centrality Analysis of the Lightning Network

Payment channel networks (PCNs) such as the Lightning Network offer an appealing solution to the scalability problem faced by many cryptocurrencies operating on a blockchain such as Bitcoin. However, PCNs also inherit the stringent dependability requirements of blockchain. In particular, in order to mitigate liquidity bottlenecks as well as on-path attacks, it is important that payment channel networks maintain a high degree of decentralization. Motivated by this requirement, we conduct an empirical centrality analysis of the popular Lightning Network, and in particular, the betweenness centrality distribution of the routing system. Based on our extensive data set (using several millions of channel update messages), we implemented a TimeMachine tool which enables us to study the network evolution over time. We find that although the network is generally fairly decentralized, a small number of nodes can attract a significant fraction of the transactions, introducing skew. Furthermore, our analysis suggests that over the last two years, the centrality has increased significantly, e.g., the inequality (measured by the Gini index) has increased by more than 10%.

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preprint2022arXiv

Deterministic Self-Adjusting Tree Networks Using Rotor Walks

We revisit the design of self-adjusting single-source tree networks. The problem can be seen as a generalization of the classic list update problem to trees, and finds applications in reconfigurable datacenter networks. We are given a fixed balanced binary tree T connecting n nodes V = {v_1, ... , v_n}. A source node v_0, attached to the root of the tree, issues communication requests to nodes in V, in an online and adversarial manner; the access cost of a request to a node v, is given by the current depth of v in T. The online algorithm can try to reduce the access cost by performing swap operations, with which the position of a node is exchanged with the position of its parent in the tree; a swap operation costs one unit. The objective is to design an online algorithm which minimizes the total access cost plus adjustment cost (swapping). Avin et al. recently presented Random-Push, a constant competitive online algorithm for this problem, based on random walks, together with an analysis exploiting the most recently used (MRU) property of random walks. We study analytically and empirically, online algorithms for this problem. In particular, we explore how to derandomize Random-Push. We consider a simple derandomized algorithm which we call Rotor-Push, as its behavior is reminiscent of rotor walks. We first prove that Rotor-Push is constant competitive: its competitive ratio is 12 and hence by a factor of five lower than the best existing competitive ratio. In contrast to Random-Push, the algorithm does not feature the MRU property, which requires a new analysis. We present a significantly improved and simpler analysis for the randomized algorithm, showing that it is 16-competitive. We compare empirically all self-adjusting single-source tree networks, using synthetic and real data with varying locality and observe that Rotor-Push and Random-Push have almost identical performance.

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preprint2022arXiv

Fast and Heavy Disjoint Weighted Matchings for Demand-Aware Datacenter Topologies

Reconfigurable optical topologies promise to improve the performance in datacenters by dynamically optimizing the physical network in a demand-aware manner. State-of-the-art optical technologies allow to establish and update direct connectivity (in the form of edge-disjoint matchings) between top-of-rack switches within microseconds or less. However, to fully exploit temporal structure in the demand, such fine-grained reconfigurations also require fast algorithms for optimizing the interconnecting matchings. Motivated by the desire to offload a maximum amount of demand to the reconfigurable network, this paper initiates the study of fast algorithms to find k disjoint heavy matchings in graphs. We present and analyze six algorithms, based on iterative matchings, b-matching, edge coloring, and node-rankings. We show that the problem is generally NP-hard and study the achievable approximation ratios. An extensive empirical evaluation of our algorithms on both real-world and synthetic traces (88 in total), including traces collected in Facebook datacenters and in HPC clusters reveals that all our algorithms provide high-quality matchings, and also very fast ones come within 95% or more of the best solution. However, the running times differ significantly and what is the best algorithm depends on k and the acceptable runtime-quality tradeoff.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Improved Throughput for All-or-Nothing Multicommodity Flows with Arbitrary Demands

Throughput is a main performance objective in communication networks. This paper considers a fundamental maximum throughput routing problem -- the all-or-nothing multicommodity flow (ANF) problem -- in arbitrary directed graphs and in the practically relevant but challenging setting where demands can be (much) larger than the edge capacities. Hence, in addition to assigning requests to valid flows for each routed commodity, an admission control mechanism is required which prevents overloading the network when routing commodities. We make several contributions. On the theoretical side we obtain substantially improved bi-criteria approximation algorithms for this NP-hard problem. We present two non-trivial linear programming relaxations and show how to convert their fractional solutions into integer solutions via randomized rounding. One is an exponential-size formulation (solvable in polynomial time using a separation oracle) that considers a "packing" view and allows a more flexible approach, while the other is a compact (polynomial-size) edge-flow formulation that allows for easy solving via standard LP solvers. We obtain a polynomial-time randomized algorithm that yields an arbitrarily good approximation on the weighted throughput, while violating the edge capacity constraints by only a small multiplicative factor. We also describe a deterministic rounding algorithm by derandomization, using the method of pessimistic estimators. We complement our theoretical results with a proof of concept empirical evaluation.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Kevin: de Bruijn-based topology with demand-aware links and greedy routing

We propose Kevin, a novel demand-aware reconfigurable rack-to-rack datacenter network realized with a simple and efficient control plane. In particular, Kevin makes effective use of the network capacity by supporting integrated and multi-hop routing as well as work-conserving scheduling. To this end, Kevin relies on local greedy routing with small forwarding tables which require local updates only during topological reconfigurations, making this approach ideal for dynamic networks. Specifically, Kevin is based on a de Bruijn topology (using a small number of optical circuit switches) in which static links are enhanced with opportunistic links.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Model-Based Insights on the Performance, Fairness, and Stability of BBR

Google's BBR is the most prominent result of the recently revived quest for efficient, fair, and flexible congestion-control algorithms (CCAs). While the performance of BBR has been investigated by numerous studies, previous work still leaves gaps in the understanding of BBR performance: Experiment-based studies generally only consider network settings that researchers can set up with manageable effort, and model-based studies neglect important issues like convergence. To complement previous BBR analyses, this paper presents a fluid model of BBRv1 and BBRv2, allowing both efficient simulation under a wide variety of network settings and analytical treatment such as stability analysis. By experimental validation, we show that our fluid model provides highly accurate predictions of BBR behavior. Through extensive simulations and theoretical analysis, we arrive at several insights into both BBR versions, including a previously unknown bufferbloat issue in BBRv2.

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preprint2022arXiv

On the Price of Locality in Static Fast Rerouting

Modern communication networks feature fully decentralized flow rerouting mechanisms which allow them to quickly react to link failures. This paper revisits the fundamental algorithmic problem underlying such local fast rerouting mechanisms. Is it possible to achieve perfect resilience, i.e., to define local routing tables which preserve connectivity as long as the underlying network is still connected? Feigenbaum et al. (ACM PODC'12) and Foerster et al. (SIAM APOCS'21) showed that, unfortunately, it is impossible in general. This paper charts a more complete landscape of the feasibility of perfect resilience. We first show a perhaps surprisingly large price of locality in static fast rerouting mechanisms: even when source and destination remain connected by a linear number of link-disjoint paths after link failures, local rerouting algorithms cannot find any of them which leads to a disconnection on the routing level. This motivates us to study resilience in graphs which exclude certain dense minors, such as cliques or a complete bipartite graphs, and in particular, provide characterizations of the possibility of perfect resilience in different routing models. We provide further insights into the price of locality by showing impossibility results for few failures and investigate perfect resilience on Topology Zoo networks.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

P4RROT: Generating P4 Code for the Application Layer

Throughput and latency critical applications could often benefit of performing computations close to the client. To enable this, distributed computing paradigms such as edge computing have recently emerged. However, with the advent of programmable data planes, computations cannot only be performed by servers but they can be offloaded to network switches. Languages like P4 enable to flexibly reprogram the entire packet processing pipeline. Though these devices promise high throughput and ultra-low response times, implementing application-layer tasks in the data plane programming language P4 is still challenging for an application developer who is not familiar with networking domain. In this paper, we first identify and examine obstacles and pain points one can experience when offloading server-based computations to the network. Then we present P4RROT, a code generator (in form of a library) which allows to overcome these limitations by providing a user-friendly API to describe computations to be offloaded. After discussing the design choices behind P4RROT, we introduce our proof-of-concept implementation for two P4 targets: Netronome SmartNIC and BMv2.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Renaissance: A Self-Stabilizing Distributed SDN Control Plane using In-band Communications

By introducing programmability, automated verification, and innovative debugging tools, Software-Defined Networks (SDNs) are poised to meet the increasingly stringent dependability requirements of today's communication networks. However, the design of fault-tolerant SDNs remains an open challenge. This paper considers the design of dependable SDNs through the lenses of self-stabilization - a very strong notion of fault-tolerance. In particular, we develop algorithms for an in-band and distributed control plane for SDNs, called Renaissance, which tolerate a wide range of failures. Our self-stabilizing algorithms ensure that after the occurrence of arbitrary failures, (i) every non-faulty SDN controller can reach any switch (or another controller) within a bounded communication delay (in the presence of a bounded number of failures) and (ii) every switch is managed by a controller. We evaluate Renaissance through a rigorous worst-case analysis as well as a prototype implementation (based on OVS and Floodlight, and Mininet).

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Sinkless Orientation Made Simple

The sinkless orientation problem plays a key role in understanding the foundations of distributed computing. The problem can be used to separate two fundamental models of distributed graph algorithms, LOCAL and SLOCAL: the locality of sinkless orientation is $Ω(\log n)$ in the deterministic LOCAL model and $O(\log \log n)$ in the deterministic SLOCAL model. Both of these results are known by prior work, but here we give new simple, self-contained proofs for them.

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preprint2022arXiv

Time Complexity of Consensus in Dynamic Networks Under Oblivious Message Adversaries

Consensus is a most fundamental task in distributed computing. This paper studies the consensus problem for a set of processes connected by a dynamic directed network, in which computation and communication is lock-step synchronous but controlled by an oblivious message adversary. In this basic model, determining consensus solvability and designing consensus algorithms in the case where it is possible, has been shown to be surprisingly difficult. We present an explicit decision procedure to determine if consensus is possible under a given adversary. This in turn enables us, for the first time, to study the time complexity of consensus in this model. In particular, we derive time complexity upper bounds for consensus solvability both for a centralized decision procedure as well as for solving distributed consensus. We complement these results with time complexity lower bounds. Intriguingly, we find that reaching consensus under an oblivious message adversary can take exponentially longer than broadcasting the input value of some process to all other processes.

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preprint2022arXiv

Weighted Packet Selection for Rechargeable Links: Complexity and Approximation

We consider a natural problem dealing with weighted packet selection across a rechargeable link, which e.g., finds applications in cryptocurrency networks. The capacity of a link $(u,v)$ is determined by how much players $u$ and $v$ allocate for this link. Specifically, the input is a finite ordered sequence of packets that arrive in both directions along a link. Given $(u, v)$ and a packet of weight $x$ going from $u$ to $v$, player $u$ can either accept or reject the packet. If player $u$ accepts the packet, their capacity on link $(u,v)$ decreases by $x$. Correspondingly, player $v$ capacity on $(u,v)$ increases by $x$. If a player rejects the packet, this will entail a cost linear in the weight of the packet. A link is "rechargeable" in the sense that the total capacity of the link has to remain constant, but the allocation of capacity at the ends of the link can depend arbitrarily on players' decisions. The goal is to minimise the sum of the capacity injected into the link and the cost of rejecting packets. We show the problem is NP-hard, but can be approximated efficiently with a ratio of $(1+ \varepsilon)\cdot (1+\sqrt{3})$ for some arbitrary $\varepsilon >0$.

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preprint2022arXiv

Wiser: Increasing Throughput in Payment Channel Networks with Transaction Aggregation

Payment channel networks (PCNs) are one of the most prominent solutions to the limited transaction throughput of blockchains. Nevertheless, PCNs suffer themselves from a throughput limitation due to the capital constraints of their channels. A similar dependence on high capital is also found in inter-bank payment settlements, where the so-called netting technique is used to mitigate liquidity demands. In this work, we alleviate this limitation by introducing the notion of transaction aggregation: instead of executing transactions sequentially through a PCN, we enable senders to aggregate multiple transactions and execute them simultaneously to benefit from several amounts that may "cancel out". Two direct advantages of our proposal is the decrease in intermediary fees paid by senders as well as the obfuscation of the transaction data from the intermediaries. We formulate the transaction aggregation as a computational problem, a generalization of the Bank Clearing Problem. We present a generic framework for the transaction aggregation execution, and thereafter we propose Wiser as an implementation of this framework in a specific hub-based setting. To overcome the NP-hardness of the transaction aggregation problem, in Wiser we propose a fixed-parameter linear algorithm for a special case of transaction aggregation as well as the Bank Clearing Problem. Wiser can also be seen as a modern variant of the Hawala money transfer system, as well as a decentralized implementation of the overseas remittance service of Wise.

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preprint2021arXiv

Between-session reliability of skin marker-derived spinal kinematics during functional activities

Background: Skin marker-based analysis of functional spinal movement is a promising method for quantifying longitudinal effects of treatment interventions in patients with spinal pathologies. However, observed day-to-day changes might not necessarily be due to a treatment intervention, but can result from errors related to soft tissue artifacts, marker placement inaccuracies or biological day-to-day variability. Research question: How reliable are skin marker-derived three-dimensional spinal kinematics during functional activities between two separate measurement sessions? Methods: Twenty healthy adults (11f/9m) were invited to a movement analysis laboratory for two visits separated by 7-10 days. At each visit, they performed various functional activities (i.e. sitting, standing, walking, running, chair rising, box lifting and vertical jumping), while marker trajectories were recorded using a skin marker-based 10-camera optical motion capture system and used to calculate sagittal and frontal plane spinal curvature angles as well as transverse plane segmental rotational angles in the lumbar and thoracic regions. Between-session reliability for continuous data and discrete parameters was determined by analyzing systematic errors using one sample T-tests as well as by calculating intraclass correlation coefficients (ICCs) and minimal detectable changes (MDCs). Results and Significance: The analysis indicated high relative consistency for sagittal plane curvature angles during all activities, but not for frontal and transverse plane angles during walking and running. MDCs were mostly below 15°, with relative values ranging between 10% and 750%. This study provides important information that can serve as a basis for researchers and clinicians aiming at investigating longitudinal effects of treatment interventions on spinal motion behavior in patients with spinal pathologies.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

From Stoop to Squat: A comprehensive analysis of lumbar loading among different lifting styles

Lifting up objects from the floor has been identified as a risk factor for low back pain, whereby a flexed spine during lifting is often associated with producing higher loads in the lumbar spine. Even though recent biomechanical studies challenge these assumptions, conclusive evidence is still lacking. This study therefore aimed at comparing lumbar loads among different lifting styles using a comprehensive state-of-the-art motion capture-driven musculoskeletal modeling approach. Thirty healthy pain-free individuals were enrolled in this study and asked to repetitively lift a 15 kg-box by applying 1) a freestyle, 2) a squat and 3) a stoop lifting technique. Whole-body kinematics were recorded using an optical motion capture system and used to drive a full-body musculoskeletal model including a detailed thoracolumbar spine. Compressive, shear and total loads were calculated based on a static optimization approach and expressed as factor body weight (BW). In addition, lumbar lordosis angles and total lifting time were calculated. All parameters were compared among the lifting styles using a repeated measures design. For all lumbar segments, stoop lifting showed significantly lower compressive and total loads (-0.3 to -1.0BW) when compared to freestyle and squat lifting. Stoop lifting produced higher shear loads (+0.1 to +0.8BW) in the segments T12/L1 to L4/L5, but lower loads in L5/S1 (-0.2 to -0.4BW). Peak compressive and total loads during squat lifting occurred approximately 30% earlier in the lifting cycle compared to stoop lifting. Stoop lifting showed larger lumbar lordosis range of motion (35.9+/-10.1°) than freestyle (24.2+/-7.3°) and squat (25.1+/-8.2°) lifting. Lifting time differed significantly with freestyle being executed the fastest (4.6+/-0.7s), followed by squat (4.9+/-0.7s) and stoop (5.9+/-1.1s).

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preprint2021arXiv

Input-Dynamic Distributed Algorithms for Communication Networks

Consider a distributed task where the communication network is fixed but the local inputs given to the nodes of the distributed system may change over time. In this work, we explore the following question: if some of the local inputs change, can an existing solution be updated efficiently, in a dynamic and distributed manner? To address this question, we define the batch dynamic CONGEST model in which we are given a bandwidth-limited communication network and a dynamic edge labelling defines the problem input. The task is to maintain a solution to a graph problem on the labeled graph under batch changes. We investigate, when a batch of $α$ edge label changes arrive, -- how much time as a function of $α$ we need to update an existing solution, and -- how much information the nodes have to keep in local memory between batches in order to update the solution quickly. Our work lays the foundations for the theory of input-dynamic distributed network algorithms. We give a general picture of the complexity landscape in this model, design both universal algorithms and algorithms for concrete problems, and present a general framework for lower bounds. In particular, we derive non-trivial upper bounds for two selected, contrasting problems: maintaining a minimum spanning tree and detecting cliques.

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preprint2021arXiv

Skin marker-based subject-specific spinal alignment modeling: A feasibility study

Musculoskeletal models have the potential to improve diagnosis and optimize clinical treatment by predicting accurate outcomes on an individual basis. However, the subject-specific modeling of spinal alignment is often strongly simplified or is based on radiographic assessments, exposing subjects to unnecessary radiation. We therefore developed a novel skin marker-based approach for modeling subject-specific spinal alignment and evaluated its feasibility by comparing the predicted with the actual intervertebral joint (IVJ) locations/orientations (ground truth) using lateral-view radiographic images. Moreover, the predictive performance of the subject-specific models was evaluated by comparing the predicted L1/L2 spinal loads during various functional activities with in vivo measured data obtained from the OrthoLoad database. IVJ locations/orientations were predicted closer to ground truth as opposed to standard model scaling, with average location prediction errors of 0.99+/-0.68 cm on the frontal and 1.21+/-0.97 cm on the transverse axis as well as an average orientation prediction error of 4.74°+/-2.80°. Simulated spinal loads showed similar curve patterns but considerably larger values as compared to in vivo measured data. Differences in spinal loads between generic and subject-specific models become only apparent on an individual subject level. These results underline the feasibility of the proposed method and associated workflow for inter- and intra-subject investigations using musculoskeletal simulations. When implemented into standard model scaling workflows, it is expected to improve the accuracy of muscle activity and joint loading simulations, which is crucial for investigations of treatment effects or pathology-dependent deviations.

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preprint2021arXiv

The Stoop-Squat-Index: a simple but powerful measure for quantifying lifting behavior

The widely held belief that squat lifting should be preferred over stoop lifting to prevent back injury is increasingly being challenged by recent biomechanical evidence. However, most of these studies only focus on very localized parameters such as lumbar spine flexion, while evaluations of whole-body lifting strategies are largely lacking. For this reason, a novel index, the Stoop-Squat-Index, was developed, which describes the proportion between trunk forward lean and lower extremity joint flexion, with possible values ranging from 0 (full squat lifting) to 100 (full stoop lifting). To enable the interpretation of the index in a real-life setting, normative values were established using motion capture data from 30 healthy pain-free individuals that were collected in the context of a previous study. The results showed mean index values of lower than 30 and higher than 90 for the most relevant phases of the squat and stoop movements, respectively, with mean index values differing significantly from each other for the full duration of the lifting phases. The main advantages of the index are that it is simple to calculate and can not only be derived from motion capture data but also from conventional video recordings, which enables large-scale in-field measurements with relatively low expenditure. When used in combination with lumbar spine flexion measurements, the index can contribute important information, which is necessary for comprehensively evaluating whole-body lifting strategies and to shed more light on the debate over the connection between lifting posture and back complaints.

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preprint2020arXiv

Conic Formation in Presence of Faulty Robots

Pattern formation is one of the most fundamental problems in distributed computing, which has recently received much attention. In this paper, we initiate the study of distributed pattern formation in situations when some robots can be \textit{faulty}. In particular, we consider the well-established \textit{look-compute-move} model with oblivious, anonymous robots. We first present lower bounds and show that any deterministic algorithm takes at least two rounds to form simple patterns in the presence of faulty robots. We then present distributed algorithms for our problem which match this bound, \textit{for conic sections}: in at most two rounds, robots form lines, circles and parabola tolerating $f=2,3$ and $4$ faults, respectively. For $f=5$, the target patterns are parabola, hyperbola and ellipse. We show that the resulting pattern includes the $f$ faulty robots in the pattern of $n$ robots, where $n \geq 2f+1$, and that $f < n < 2f+1$ robots cannot form such patterns. We conclude by discussing several relaxations and extensions.

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preprint2020arXiv

Dynamic Balanced Graph Partitioning

This paper initiates the study of the classic balanced graph partitioning problem from an online perspective: Given an arbitrary sequence of pairwise communication requests between $n$ nodes, with patterns that may change over time, the objective is to service these requests efficiently by partitioning the nodes into $\ell$ clusters, each of size $k$, such that frequently communicating nodes are located in the same cluster. The partitioning can be updated dynamically by migrating nodes between clusters. The goal is to devise online algorithms which jointly minimize the amount of inter-cluster communication and migration cost. The problem features interesting connections to other well-known online problems. For example, scenarios with $\ell=2$ generalize online paging, and scenarios with $k=2$ constitute a novel online variant of maximum matching. We present several lower bounds and algorithms for settings both with and without cluster-size augmentation. In particular, we prove that any deterministic online algorithm has a competitive ratio of at least $k$, even with significant augmentation. Our main algorithmic contributions are an $O(k \log{k})$-competitive deterministic algorithm for the general setting with constant augmentation, and a constant competitive algorithm for the maximum matching variant.

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preprint2020arXiv

Measuring lumbar back motion during functional activities using a portable strain gauge sensor-based system: a comparative evaluation and reliability study

Quantifying lumbar back motion during functional activities in real-life environments may contribute to a better understanding of common pathologies such as spinal disorders. The current study therefore aimed at the comparative evaluation of the Epionics SPINE system, a portable device for measuring sagittal lumbar back motion during functional activities. Twenty healthy participants were therefore evaluated with the Epionics SPINE and a Vicon motion capture system in two identical separate research visits. They performed the following activities: standing, sitting, chair rising, box lifting, walking, running and a counter movement jump (CMJ). Lumbar lordosis angles were extracted as continuous values as well as average and range of motion (ROM) parameters. Agreement between the systems was evaluated using Bland-Altman analyses, whereas within- and between-session reliability were assessed using intraclass correlation coefficients (ICC) and minimal detectable changes (MDC). The analysis showed excellent agreement between the systems for chair rising, box lifting and CMJ with a systematic underestimation of lumbar lordosis angles during walking and running. Reliability was moderate to high for all continuous and discrete parameters (ICC>=0.62), except for ROM during running (ICC=0.29). MDC values were generally below 15°, except for CMJ (peak values up to 20° within and 25° between the sessions). The Epionics SPINE system performed similarly to a Vicon motion capture system for measuring lumbar lordosis angles during functional activities and showed high consistency within and between measurement sessions. These findings can serve researchers and clinicians as a bench mark for future investigations using the system in populations with spinal pathologies.

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preprint2020arXiv

Musculoskeletal full-body models including a detailed thoracolumbar spine for children and adolescents aged 6-18 years

Currently available musculoskeletal inverse-dynamics thoracolumbar spine models are entirely based on data from adults and might therefore not be applicable for simulations in children and adolescents. In addition, these models lack lower extremities, which are required for comprehensive evaluations of functional activities or therapeutic exercises. We therefore created OpenSim-based musculoskeletal full-body models including a detailed thoracolumbar spine for children and adolescents aged 6-18 years and validated by comparing model predictions to in vivo data. After combining our recently developed adult thoracolumbar spine model with a lower extremity model, children and adolescent models were created for each year of age by adjusting segmental length and mass distribution, center of mass positions and moments of inertia of the major body segments as well as sagittal pelvis and spine alignment based on literature data. Similarly, muscle strength properties were adjusted based on CT-derived cross-sectional area measurements. Simulations were conducted from in vivo studies reported in the literature involving children and adolescents evaluating maximum trunk muscle strength (MTMS), lumbar disc compressibility (LDC), intradiscal pressure (IDP) and trunk muscle activity (MA). Model predictions correlated highly with in vivo data (MTMS: r>=0.82, p<=0.03; LDC: r=0.77, p<0.001; IDP: r>=0.78, p<0.001; MA: r>=0.90, p<0.001), indicating suitability for the reasonably accurate prediction of maximal trunk muscle strength, segmental loading and trunk muscle activity in children and adolescents. When aiming at investigating children or adolescents with pathologies such as idiopathic scoliosis, our models can serve as a basis for the creation of deformed spine models and for comparative purposes.

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preprint2020arXiv

On Search Friction of Route Discovery in Offchain Networks

Offchain networks provide a promising solution to overcome the scalability challenges of cryptocurrencies. However, design tradeoffs of offchain networks are still not well-understood today. In particular, offchain networks typically rely on fees-based incentives and hence require mechanisms for the efficient discovery of ``good routes'': routes with low fees (cost efficiency) and a high success rate of the transaction routing (effectiveness). Furthermore, the route discovery should be confidential (privacy), and e.g., not reveal information about who transacts with whom or about the transaction value. This paper provides an analysis of the ``search friction'' of route discovery, i.e., the costs and tradeoffs of route discovery in large-scale offchain networks in which nodes behave strategically. As a case study, we consider the Lighning network and the route discovery service provided by the trampoline nodes, evaluating the tradeoff in different scenarios also empirically. Finally, we initiate the discussion of alternative charging schemes for offchain networks.

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preprint2020arXiv

Push-Down Trees: Optimal Self-Adjusting Complete Trees

This paper studies a fundamental algorithmic problem related to the design of demand-aware networks: networks whose topologies adjust toward the traffic patterns they serve, in an online manner. The goal is to strike a tradeoff between the benefits of such adjustments (shorter routes) and their costs (reconfigurations). In particular, we consider the problem of designing a self-adjusting tree network which serves single-source, multi-destination communication. The problem has interesting connections to self-adjusting datastructures. We present two constant-competitive online algorithms for this problem, one randomized and one deterministic. Our approach is based on a natural notion of Most Recently Used (MRU) tree, maintaining a working set. We prove that the working set is a cost lower bound for any online algorithm, and then present a randomized algorithm RANDOM-PUSH which approximates such an MRU tree at low cost, by pushing less recently used communication partners down the tree, along a random walk. Our deterministic algorithm MOVE-HALF does not directly maintain an MRU tree, but its cost is still proportional to the cost of an MRU tree, and also matches the working set lower bound.

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preprint2020arXiv

Spinal Compressive Forces in Adolescent Idiopathic Scoliosis With and Without Carrying Loads: A Musculoskeletal Modeling Study

The pathogenesis of adolescent idiopathic scoliosis (AIS) remains poorly understood and biomechanical data are limited. A deeper insight into spinal loading could provide valuable information for the improvement of current treatment strategies. This work therefore aimed at using subject-specific musculoskeletal full-body models of patients with AIS to predict segmental compressive forces around the curve apex and to investigate how these forces are affected by simulated load carrying. Models were created based on spatially calibrated biplanar radiographic images from 24 patients with mild to moderate AIS and validated by comparing predictions of paravertebral muscle activity with reported values from in vivo studies. Spinal compressive forces were predicted during unloaded upright standing as well as upright standing with external loads of 10%, 15% and 20% of body weight (BW) applied to the scapulae to simulate carrying a backpack in the regular way, in front of the body and over both shoulders. The validation studies showed higher convex muscle activity, which was comparable to the literature. The implementation of spinal deformity resulted in a 10% increase of compressive force at the curve apex during unloaded upright standing. Apical compressive forces further increased by 50-62%, 77-94% and 103-128% for 10%, 15% and 20% BW loads, respectively. Moreover, load-dependent compressive force increases were the lowest in the regular backpack and the highest in the frontpack and convex conditions. The predictions indicated increased segmental compressive forces during unloaded standing, which could be ascribed to the scoliotic deformation. When carrying loads, compressive forces further increased depending on the carrying mode and the weight of the load. These results can be used as a basis for further studies investigating segmental loading in AIS patients during functional activities.

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preprint2020arXiv

Survey on Cryptocurrency Networking: Context, State-of-the-Art, Challenges

Cryptocurrencies such as Bitcoin are realized using distributed systems and hence critically rely on the performance and security of the interconnecting network. The requirements on these networks and their usage, however can differ significantly from traditional communication networks, with implications on all layers of the protocol stack. This paper is motivated by these differences, and in particular by the observation that many fundamental design aspects of these networks are not well-understood today. In order to support the networking community to contribute to this emerging application domain, we present a structured overview of the field, from topology and neighbor discovery to block and transaction propagation. In particular, we provide the context, highlighting differences and commonalities with traditional networks, review the state-of-the-art, and identify open research challenges. Our paper can hence also be seen as a call-to-arms to improve the foundation on top of which cryptocurrencies are built.

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preprint2020arXiv

The Value of Information in Selfish Routing

Path selection by selfish agents has traditionally been studied by comparing social optima and equilibria in the Wardrop model, i.e., by investigating the Price of Anarchy in selfish routing. In this work, we refine and extend the traditional selfish-routing model in order to answer questions that arise in emerging path-aware Internet architectures. The model enables us to characterize the impact of different degrees of congestion information that users possess. Furthermore, it allows us to analytically quantify the impact of selfish routing, not only on users, but also on network operators. Based on our model, we show that the cost of selfish routing depends on the network topology, the perspective (users versus network operators), and the information that users have. Surprisingly, we show analytically and empirically that less information tends to lower the Price of Anarchy, almost to the optimum. Our results hence suggest that selfish routing has modest social cost even without the dissemination of path-load information.

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preprint2020arXiv

Toward Active and Passive Confidentiality Attacks On Cryptocurrency Off-Chain Networks

Cryptocurrency off-chain networks such as Lightning (e.g., Bitcoin) or Raiden (e.g., Ethereum) aim to increase the scalability of traditional on-chain transactions. To support nodes in learning about possible paths to route their transactions, these networks need to provide gossip and probing mechanisms. This paper explores whether these mechanisms may be exploited to infer sensitive information about the flow of transactions, and eventually harm privacy. In particular, we identify two threats, related to an active and a passive adversary. The first is a probing attack: here the adversary aims to detect the maximum amount which is transferable in a given direction over a target channel by actively probing it and differentiating the response messages it receives. The second is a timing attack: the adversary discovers how close the destination of a routed payment actually is, by acting as a passive man-in-the middle and analyzing the time deltas between sent messages and their corresponding responses. We then analyze the limitations of these attacks and propose remediations for scenarios in which they are able to produce accurate results.

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preprint2020arXiv

Towards Fine-Grained Billing For Cloud Networking

We revisit multi-tenant network virtualization in data centers, and make the case for tenant-specific virtual switches. In particular, tenant-specific virtual switches allow cloud providers to extend fine-grained billing (known, e.g., from serverless architectures) to the network, accounting not only for IO, but also CPU or energy. We sketch an architecture and present economical motivation and recent technological enablers. We also find that virtual switches today do not offer sufficient multi-tenancy and can introduce artificial performance bottlenecks, e.g., in load balancers. We conclude by discussing additional use cases for tentant-specific switches.

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preprint2020arXiv

Towards Runtime Verification of Programmable Switches

Is it possible to patch software bugs in P4 programs without human involvement? We show that this is partially possible in many cases due to advances in software testing and the structure of P4 programs. Our insight is that runtime verification can detect bugs, even those that are not detected at compile-time, with machine learning-guided fuzzing. This enables a more automated and real-time localization of bugs in P4 programs using software testing techniques like Tarantula. Once the bug in a P4 program is localized, the faulty code can be patched due to the programmable nature of P4. In addition, platform-dependent bugs can be detected. From P4_14 to P4_16 (latest version), our observation is that as the programmable blocks increase, the patchability of P4 programs increases accordingly. To this end, we design, develop, and evaluate P6 that (a) detects, (b) localizes, and (c) patches bugs in P4 programs with minimal human interaction. P6 tests P4 switch non-intrusively, i.e., requires no modification to the P4 program for detecting and localizing bugs. We used a P6 prototype to detect and patch seven existing bugs in eight publicly available P4 application programs deployed on two different switch platforms: behavioral model (bmv2) and Tofino. Our evaluation shows that P6 significantly outperforms bug detection baselines while generating fewer packets and patches bugs in P4 programs such as switch.p4 without triggering any regressions.

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preprint2020arXiv

Walking and running with non-specific chronic low back pain: what about the lumbar lordosis angle?

Non-specific chronic low back pain (NSCLBP) is a major health problem, affecting about one fifth of the population worldwide. To avoid further pain or injury, patients with NSCLBP seem to adopt a stiffer movement pattern during everyday living activities. However, it remains unknown how NSCLBP affects the lumbar lordosis angle (LLA) during repetitive activities such as walking or running. This pilot study therefore aimed at exploring possible NSCLBP-related alterations in LLAs during walking and running by focusing on discrete parameters as well as continuous data. Thirteen patients with NSCLBP and 20 healthy pain-free controls were enrolled and underwent a full-body movement analysis involving various everyday living activities such as standing, walking and running. LLAs were derived from markers placed on the spinous processes of the vertebrae L1-L5 and S1. Possible group differences in discrete (average and range of motion (ROM)) and continuous LLAs were analyzed descriptively using mean differences with confidence intervals ranging from 95% to 75%. Patients with NSCLBP indicated reduced average LLAs during standing, walking and running and a tendency for lower LLA-ROM during walking. Analyses of continuous data indicated the largest group differences occurring around 25% and 70% of the walking and 25% and 75% of the running cycle. Furthermore, patients indicated a reversed movement pattern during running, with increasing instead of a decreasing LLAs after foot strike. This study provides preliminary evidence that NSCLBP might affect LLAs during walking and running. These results can be used as a basis for future large-scale investigations involving hypothesis testing.

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preprint2016arXiv

A local constant factor approximation for the minimum dominating set problem on bounded genus graphs

The Minimum Dominating Set (MDS) problem is not only one of the most fundamental problems in distributed computing, it is also one of the most challenging ones. While it is well-known that minimum dominating sets cannot be approximated locally on general graphs, over the last years, several breakthroughs have been made on computing local approximations on sparse graphs. This paper presents a deterministic and local constant factor approximation for minimum dominating sets on bounded genus graphs, a very large family of sparse graphs. Our main technical contribution is a new analysis of a slightly modified, first-order definable variant of an existing algorithm by Lenzen et al. Interestingly, unlike existing proofs for planar graphs, our analysis does not rely on any topological arguments. We believe that our techniques can be useful for the study of local problems on sparse graphs beyond the scope of this paper.

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preprint2016arXiv

An Approximation Algorithm for Path Computation and Function Placement in SDNs

We consider the task of computing (combined) function mapping and routing for requests in Software-Defined Networks (SDNs). Function mapping refers to the assignment of nodes in the substrate network to various processing stages that requests must undergo. Routing refers to the assignment of a path in the substrate network that begins in a source node of the request, traverses the nodes that are assigned functions for this request, and ends in a destination of the request. The algorithm either rejects a request or completely serves a request, and its goal is to maximize the sum of the benefits of the served requests. The solution must abide edge and vertex capacities. We follow the framework suggested by Even for the specification of the processing requirements and routing of requests via processing-and-routing graphs (PR-graphs). In this framework, each request has a demand, a benefit, and PR-graph. Our main result is a randomized approximation algorithm for path computation and function placement with the following guarantee. Let $m$ denote the number of links in the substrate network, $\eps$ denote a parameter such that $0< \eps <1$, and $\opt_f$ denote the maximum benefit that can be attained by a fractional solution (one in which requests may be partly served and flow may be split along multiple paths). Let $\cmin$ denote the minimum edge capacity, and let $\dmax$ denote the maximum demand. Let $\Deltamax$ denote an upper bound on the number of processing stages a request undergoes. If $\cmin/(\Deltamax\cdot\dmax)=Ω((\log m)/\eps^2)$, then with probability at least $1-\frac{1}{m}-\textit{exp}(-Ω(\eps^2\cdot \opt_f /(\bmax \cdot \dmax)))$, the algorithm computes a $(1-\eps)$-approximate solution.

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preprint2016arXiv

Control Exchange Points: Providing QoS-enabled End-to-End Services via SDN-based Inter-domain Routing Orchestration

This paper presents the vision of the Control Exchange Point (CXP) architectural model. The model is motivated by the inflexibility and ossification of today's inter-domain routing system, which renders critical QoS-constrained end-to-end (e2e) network services difficult or simply impossible to provide. CXPs operate on slices of ISP networks and are built on basic Software Defined Networking (SDN) principles, such as the clean decoupling of the routing control plane from the data plane and the consequent logical centralization of control. The main goal of the architectural model is to provide e2e services with QoS constraints across domains. This is achieved through defining a new type of business relationship between ISPs, which advertise partial paths (so-called pathlets) with specific properties, and the orchestrating role of the CXPs, which dynamically stitch them together and provision e2e QoS. Revenue from value-added services flows from the clients of the CXP to the ISPs participating in the service. The novelty of the approach is the combination of SDN programmability and dynamic path stitching techniques for inter-domain routing, which extends the value proposition of SDN over multiple domains. We first describe the challenges related to e2e service provision with the current inter-domain routing and peering model, and then continue with the benefits of our approach. Subsequently, we describe the CXP model in detail and report on an initial feasibility analysis.

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preprint2016arXiv

Convergence of Even Simpler Robots without Location Information

The design of distributed gathering and convergence algorithms for tiny robots has recently received much attention. In particular, it has been shown that convergence problems can even be solved for very weak, \emph{oblivious} robots: robots which cannot maintain state from one round to the next. The oblivious robot model is hence attractive from a self-stabilization perspective, where state is subject to adversarial manipulation. However, to the best of our knowledge, all existing robot convergence protocols rely on the assumption that robots, despite being "weak", can measure distances. We in this paper initiate the study of convergence protocols for even simpler robots, called \emph{monoculus robots}: robots which cannot measure distances. In particular, we introduce two natural models which relax the assumptions on the robots' cognitive capabilities: (1) a Locality Detection ($\mathcal{LD}$) model in which a robot can only detect whether another robot is closer than a given constant distance or not, (2) an Orthogonal Line Agreement ($\mathcal{OLA}$) model in which robots only agree on a pair of orthogonal lines (say North-South and West-East, but without knowing which is which). The problem turns out to be non-trivial, and simple median and angle bisection strategies can easily increase the distances among robots (e.g., the area of the enclosing convex hull) over time. Our main contribution are deterministic self-stabilizing convergence algorithms for these two models, together with a complexity analysis. We also show that in some sense, the assumptions made in our models are minimal: by relaxing the assumptions on the \textit{monoculus robots} further, we run into impossibility results.

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preprint2016arXiv

Investigating the Potential of the Inter-IXP Multigraph for the Provisioning of Guaranteed End-to-End Services

In this work, we propose utilizing the rich connectivity between IXPs and ISPs for inter-domain path stitching, supervised by centralized QoS brokers. In this context, we highlight a novel abstraction of the Internet topology, i.e., the inter-IXP multigraph composed of IXPs and paths crossing the domains of their shared member ISPs. This can potentially serve as a dense Internet-wide substrate for provisioning guaranteed end-to-end (e2e) services with high path diversity and global IPv4 address space reach. We thus map the IXP multigraph, evaluate its potential, and introduce a rich algorithmic framework for path stitching on such graph structures.

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preprint2016arXiv

PRI: Privacy Preserving Inspection of Encrypted Network Traffic

Traffic inspection is a fundamental building block of many security solutions today. For example, to prevent the leakage or exfiltration of confidential insider information, as well as to block malicious traffic from entering the network, most enterprises today operate intrusion detection and prevention systems that inspect traffic. However, the state-of-the-art inspection systems do not reflect well the interests of the different involved autonomous roles. For example, employees in an enterprise, or a company outsourcing its network management to a specialized third party, may require that their traffic remains confidential, even from the system administrator. Moreover, the rules used by the intrusion detection system, or more generally the configuration of an online or offline anomaly detection engine, may be provided by a third party, e.g., a security research firm, and can hence constitute a critical business asset which should be kept confidential. Today, it is often believed that accounting for these additional requirements is impossible, as they contradict efficiency and effectiveness. We in this paper explore a novel approach, called Privacy Preserving Inspection (PRI), which provides a solution to this problem, by preserving privacy of traffic inspection and confidentiality of inspection rules and configurations, and e.g., also supports the flexible installation of additional Data Leak Prevention (DLP) rules specific to the company.

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preprint2016arXiv

Routing-Verification-as-a-Service (RVaaS): Trustworthy Routing Despite Insecure Providers

Computer networks today typically do not provide any mechanisms to the users to learn, in a reliable manner, which paths have (and have not) been taken by their packets. Rather, it seems inevitable that as soon as a packet leaves the network card, the user is forced to trust the network provider to forward the packets as expected or agreed upon. This can be undesirable, especially in the light of today's trend toward more programmable networks: after a successful cyber attack on the network management system or Software-Defined Network (SDN) control plane, an adversary in principle has complete control over the network. This paper presents a low-cost and efficient solution to detect misbehaviors and ensure trustworthy routing over untrusted or insecure providers, in particular providers whose management system or control plane has been compromised (e.g., using a cyber attack). We propose Routing-Verification-as-a-Service (RVaaS): RVaaS offers clients a flexible interface to query information relevant to their traffic, while respecting the autonomy of the network provider. RVaaS leverages key features of OpenFlow-based SDNs to combine (passive and active) configuration monitoring, logical data plane verification and actual in-band tests, in a novel manner.

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preprint2016arXiv

Service Chain and Virtual Network Embeddings: Approximations using Randomized Rounding

The SDN and NFV paradigms enable novel network services which can be realized and embedded in a flexible and rapid manner. For example, SDN can be used to flexibly steer traffic from a source to a destination through a sequence of virtualized middleboxes, in order to realize so-called service chains. The service chain embedding problem consists of three tasks: admission control, finding suitable locations to allocate the virtualized middleboxes and computing corresponding routing paths. This paper considers the offline batch embedding of multiple service chains. Concretely, we consider the objectives of maximizing the profit by embedding an optimal subset of requests or minimizing the costs when all requests need to be embedded. Interestingly, while the service chain embedding problem has recently received much attention, so far, only non- polynomial time algorithms (based on integer programming) as well as heuristics (which do not provide any formal guarantees) are known. This paper presents the first polynomial time service chain approximation algorithms both for the case with admission and without admission control. Our algorithm is based on a novel extension of the classic linear programming and randomized rounding technique, which may be of independent interest. In particular, we show that our approach can also be extended to more complex service graphs, containing cycles or sub-chains, hence also providing new insights into the classic virtual network embedding problem.

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preprint2016arXiv

Stitching Inter-Domain Paths over IXPs

Modern Internet applications, from HD video-conferencing to health monitoring and remote control of power-plants, pose stringent demands on network latency, bandwidth and availability. An approach to support such applications and provide inter-domain guarantees, enabling new avenues for innovation, is using centralized inter-domain routing brokers. These entities centralize routing control for mission-critical traffic across domains, working in parallel to BGP. In this work, we propose using IXPs as natural points for stitching inter-domain paths under the control of inter-domain routing brokers. To evaluate the potential of this approach, we first map the global substrate of inter-IXP pathlets that IXP members could offer, based on measurements for 229 IXPs worldwide. We show that using IXPs as stitching points has two useful properties. Up to 91 % of the total IPv4 address space can be served by such inter-domain routing brokers when working in concert with just a handful of large IXPs and their associated ISP members. Second, path diversity on the inter-IXP graph increases by up to 29 times, as compared to current BGP valley-free routing. To exploit the rich path diversity, we introduce algorithms that inter-domain routing brokers can use to embed paths, subject to bandwidth and latency constraints. We show that our algorithms scale to the sizes of the measured graphs and can serve diverse simulated path request mixes. Our work highlights a novel direction for SDN innovation across domains, based on logically centralized control and programmable IXP fabrics.

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preprint2016arXiv

Transiently Consistent SDN Updates: Being Greedy is Hard

The software-defined networking paradigm introduces interesting opportunities to operate networks in a more flexible, optimized, yet formally verifiable manner. Despite the logically centralized control, however, a Software-Defined Network (SDN) is still a distributed system, with inherent delays between the switches and the controller. Especially the problem of changing network configurations in a consistent manner, also known as the consistent network update problem, has received much attention over the last years. In particular, it has been shown that there exists an inherent tradeoff between update consistency and speed. This paper revisits the problem of updating an SDN in a transiently consistent, loop-free manner. First, we rigorously prove that computing a maximum (greedy) loop-free network update is generally NP-hard; this result has implications for the classic maximum acyclic subgraph problem (the dual feedback arc set problem) as well. Second, we show that for special problem instances, fast and good approximation algorithms exist.

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preprint2016arXiv

WNetKAT: A Weighted SDN Programming and Verification Language

Programmability and verifiability lie at the heart of the software-defined networking paradigm. While OpenFlow and its match-action concept provide primitive operations to manipulate hardware configurations, over the last years, several more expressive network programming languages have been developed. This paper presents WNetKAT, the first network programming language accounting for the fact that networks are inherently weighted, and communications subject to capacity constraints (e.g., in terms of bandwidth) and costs (e.g., latency or monetary costs). WNetKAT is based on a syntactic and semantic extension of the NetKAT algebra. We demonstrate several relevant applications for WNetKAT, including cost- and capacity-aware reachability, as well as quality-of-service and fairness aspects. These applications do not only apply to classic, splittable and unsplittable (s; t)-flows, but also generalize to more complex network functions and service chains. For example, WNetKAT allows to model flows which need to traverse certain waypoint functions, which may change the traffic rate. This paper also shows the relation between the equivalence problem of WNetKAT and the equivalence problem of the weighted finite automata, which implies undecidability of the former. However, this paper also succeeds to prove the decidability of another useful problem, which is sufficient in many practical scnearios: whether an expression equals to 0. Moreover, we initiate the discussion of decidable subsets of the whole language.

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preprint2015arXiv

Hardness of Virtual Network Embedding with Replica Selection

Efficient embedding virtual clusters in physical network is a challenging problem. In this paper we consider a scenario where physical network has a structure of a balanced tree. This assumption is justified by many real- world implementations of datacenters. We consider an extension to virtual cluster embedding by introducing replication among data chunks. In many real-world applications, data is stored in distributed and redundant way. This assumption introduces additional hardness in deciding what replica to process. By reduction from classical NP-complete problem of Boolean Satisfia- bility, we show limits of optimality of embedding. Our result holds even in trees of edge height bounded by three. Also, we show that limiting repli- cation factor to two replicas per chunk type does not make the problem simpler.

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preprint2015arXiv

Online Admission Control and Embedding of Service Chains

The virtualization and softwarization of modern computer networks enables the definition and fast deployment of novel network services called service chains: sequences of virtualized network functions (e.g., firewalls, caches, traffic optimizers) through which traffic is routed between source and destination. This paper attends to the problem of admitting and embedding a maximum number of service chains, i.e., a maximum number of source-destination pairs which are routed via a sequence of to-be-allocated, capacitated network functions. We consider an Online variant of this maximum Service Chain Embedding Problem, short OSCEP, where requests arrive over time, in a worst-case manner. Our main contribution is a deterministic O(log L)-competitive online algorithm, under the assumption that capacities are at least logarithmic in L. We show that this is asymptotically optimal within the class of deterministic and randomized online algorithms. We also explore lower bounds for offline approximation algorithms, and prove that the offline problem is APX-hard for unit capacities and small L > 2, and even Poly-APX-hard in general, when there is no bound on L. These approximation lower bounds may be of independent interest, as they also extend to other problems such as Virtual Circuit Routing. Finally, we present an exact algorithm based on 0-1 programming, implying that the general offline SCEP is in NP and by the above hardness results it is NP-complete for constant L.

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preprint2015arXiv

Opposites Attract: Virtual Cluster Embedding for Profit

It is well-known that cloud application performance critically depends on the network. Accordingly, new abstractions for cloud applications are proposed which extend the performance isolation guarantees to the network. The most common abstraction is the Virtual Cluster V C(n, b): the n virtual machines of a customer are connected to a virtual switch at bandwidth b. However, today, not much is known about how to efficiently embed and price virtual clusters. This paper makes two contributions. (1) We present an algorithm called Tetris that efficiently embeds virtual clusters arriving in an online fashion, by jointly optimizing the node and link resources. We show that this algorithm allows to multiplex more virtual clusters over the same physical infrastructure compared to existing algorithms, hence improving the provider profit. (2) We present the first demand-specific pricing model called DSP for virtual clusters. Our pricing model is fair in the sense that a customer only needs to pay for what he or she asked. Moreover, it features other desirable properties, such as price independence from mapping locations.

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preprint2015arXiv

Service Provider DevOps network capabilities and tools

This report provides an understanding of how the UNIFY Service Provider (SP)-DevOps concept can be applied and integrated with a combined cloud and transport network NFV architecture. Specifically, the report contains technical descriptions of a set of novel SP-DevOps tools and support functions that facilitate observability, troubleshooting, verification, and VNF development processes. The tools and support functions are described in detail together with their architectural mapping, giving a wider understanding of the SP-DevOps concept as a whole, and how SP-DevOps tools can be used for supporting orchestration and programmability in the UNIFY NFV framework. The concept is further exemplified in a case study for deployment and scaling of an Elastic Firewall.

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preprint2014arXiv

A Distributed SDN Control Plane for Consistent Policy Updates

Software-defined networking (SDN) is a novel paradigm that out-sources the control of packet-forwarding switches to a set of software controllers. The most fundamental task of these controllers is the correct implementation of the \emph{network policy}, i.e., the intended network behavior. In essence, such a policy specifies the rules by which packets must be forwarded across the network. This paper studies a distributed SDN control plane that enables \emph{concurrent} and \emph{robust} policy implementation. We introduce a formal model describing the interaction between the data plane and a distributed control plane (consisting of a collection of fault-prone controllers). Then we formulate the problem of \emph{consistent} composition of concurrent network policy updates (short: the \emph{CPC Problem}). To anticipate scenarios in which some conflicting policy updates must be rejected, we enable the composition via a natural \emph{transactional} interface with all-or-nothing semantics. We show that the ability of an $f$-resilient distributed control plane to process concurrent policy updates depends on the tag complexity, i. e., the number of policy labels (a.k.a. \emph{tags}) available to the controllers, and describe a CPC protocol with optimal tag complexity $f+2$.

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preprint2014arXiv

Large Cuts with Local Algorithms on Triangle-Free Graphs

We study the problem of finding large cuts in $d$-regular triangle-free graphs. In prior work, Shearer (1992) gives a randomised algorithm that finds a cut of expected size $(1/2 + 0.177/\sqrt{d})m$, where $m$ is the number of edges. We give a simpler algorithm that does much better: it finds a cut of expected size $(1/2 + 0.28125/\sqrt{d})m$. As a corollary, this shows that in any $d$-regular triangle-free graph there exists a cut of at least this size. Our algorithm can be interpreted as a very efficient randomised distributed algorithm: each node needs to produce only one random bit, and the algorithm runs in one synchronous communication round. This work is also a case study of applying computational techniques in the design of distributed algorithms: our algorithm was designed by a computer program that searched for optimal algorithms for small values of $d$.

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preprint2014arXiv

Modeling and Measuring Graph Similarity: The Case for Centrality Distance

The study of the topological structure of complex networks has fascinated researchers for several decades, and today we have a fairly good understanding of the types and reoccurring characteristics of many different complex networks. However, surprisingly little is known today about models to compare complex graphs, and quantitatively measure their similarity. This paper proposes a natural similarity measure for complex networks: centrality distance, the difference between two graphs with respect to a given node centrality. Centrality distances allow to take into account the specific roles of the different nodes in the network, and have many interesting applications. As a case study, we consider the closeness centrality in more detail, and show that closeness centrality distance can be used to effectively distinguish between randomly generated and actual evolutionary paths of two dynamic social networks.

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preprint2014arXiv

Urban Mobility Scaling: Lessons from `Little Data'

Recent mobility scaling research, using new data sources, often relies on aggregated data alone. Hence, these studies face difficulties characterizing the influence of factors such as transportation mode on mobility patterns. This paper attempts to complement this research by looking at a category-rich mobility data set. In order to shed light on the impact of categories, as a case study, we use conventionally collected German mobility data. In contrast to `check-in'-based data, our results are not biased by Euclidean distance approximations. In our analysis, we show that aggregation can hide crucial differences between trip length distributions, when subdivided by categories. For example, we see that on an urban scale (0 to ~15 km), walking, versus driving, exhibits a highly different scaling exponent, thus universality class. Moreover, mode share and trip length are responsive to day-of-week and time-of-day. For example, in Germany, although driving is relatively less frequent on Sundays than on Wednesdays, trips seem to be longer. In addition, our work may shed new light on the debate between distance-based and intervening-opportunity mechanisms affecting mobility patterns, since mode may be chosen both according to trip length and urban form.

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preprint2013arXiv

A Federated CloudNet Architecture: The PIP and the VNP Role

We present a generic and flexible architecture to realize CloudNets: virtual networks connecting cloud resources with resource guarantees. Our architecture is federated and supports different (and maybe even competing) economical roles, by providing explicit negotiation and provisioning interfaces. Contract-based interactions and a resource description language that allows for aggregation and abstraction, preserve the different roles' autonomy without sacrificing flexibility. Moreover, since our CloudNet architecture is plugin based, essentially all cloud operating systems (e.g., OpenStack) or link technologies (e.g., VLANs, OpenFlow, VPLS) can be used within the framework. This paper describes two roles in more detail: The Physical Infrastructure Providers (PIP) which own the substrate network and resources, and the Virtual Network Providers (VNP) which can act as resource and CloudNet brokers and resellers. Both roles are fully implemented in our wide-area prototype that spans remote sites and resources.

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preprint2013arXiv

Competitive MAC under Adversarial SINR

This paper considers the problem of how to efficiently share a wireless medium which is subject to harsh external interference or even jamming. While this problem has already been studied intensively for simplistic single-hop or unit disk graph models, we make a leap forward and study MAC protocols for the SINR interference model (a.k.a. the physical model). We make two contributions. First, we introduce a new adversarial SINR model which captures a wide range of interference phenomena. Concretely, we consider a powerful, adaptive adversary which can jam nodes at arbitrary times and which is only limited by some energy budget. The second contribution of this paper is a distributed MAC protocol which provably achieves a constant competitive throughput in this environment: we show that, with high probability, the protocol ensures that a constant fraction of the non-blocked time periods is used for successful transmissions.

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preprint2013arXiv

How (Not) to Shoot in Your Foot with SDN Local Fast Failover: A Load-Connectivity Tradeoff

This paper studies the resilient routing and (in-band) fast failover mechanisms supported in Software-Defined Networks (SDN). We analyze the potential benefits and limitations of such failover mechanisms, and focus on two main metrics: (1) correctness (in terms of connectivity and loop-freeness) and (2) load-balancing. We make the following contributions. First, we show that in the worst-case (i.e., under adversarial link failures), the usefulness of local failover is rather limited: already a small number of failures will violate connectivity properties under any fast failover policy, even though the underlying substrate network remains highly connected. We then present randomized and deterministic algorithms to compute resilient forwarding sets; these algorithms achieve an almost optimal tradeoff. Our worst-case analysis is complemented with a simulation study.

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preprint2013arXiv

OBST: A Self-Adjusting Peer-to-Peer Overlay Based on Multiple BSTs

The design of scalable and robust overlay topologies has been a main research subject since the very origins of peer-to-peer (p2p) computing. Today, the corresponding optimization tradeoffs are fairly well-understood, at least in the static case and from a worst-case perspective. This paper revisits the peer-to-peer topology design problem from a self-organization perspective. We initiate the study of topologies which are optimized to serve the communication demand, or even self-adjusting as demand changes. The appeal of this new paradigm lies in the opportunity to be able to go beyond the lower bounds and limitations imposed by a static, communication-oblivious, topology. For example, the goal of having short routing paths (in terms of hop count) does no longer conflict with the requirement of having low peer degrees. We propose a simple overlay topology Obst(k) which is composed of k (rooted and directed) Binary Search Trees (BSTs), where k is a parameter. We first prove some fundamental bounds on what can and cannot be achieved optimizing a topology towards a static communication pattern (a static Obst(k)). In particular, we show that the number of BSTs that constitute the overlay can have a large impact on the routing costs, and that a single additional BST may reduce the amortized communication costs from Omega(log(n)) to O(1), where n is the number of peers. Subsequently, we discuss a natural self-adjusting extension of Obst(k), in which frequently communicating partners are "splayed together".

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preprint2013arXiv

Request Complexity of VNet Topology Extraction: Dictionary-Based Attacks

The network virtualization paradigm envisions an Internet where arbitrary virtual networks (VNets) can be specified and embedded over a shared substrate (e.g., the physical infrastructure). As VNets can be requested at short notice and for a desired time period only, the paradigm enables a flexible service deployment and an efficient resource utilization. This paper investigates the security implications of such an architecture. We consider a simple model where an attacker seeks to extract secret information about the substrate topology, by issuing repeated VNet embedding requests. We present a general framework that exploits basic properties of the VNet embedding relation to infer the entire topology. Our framework is based on a graph motif dictionary applicable for various graph classes. Moreover, we provide upper bounds on the request complexity, the number of requests needed by the attacker to succeed.

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preprint2013arXiv

Simple Destination-Swap Strategies for Adaptive Intra- and Inter-Tenant VM Migration

This paper investigates the opportunities and limitations of adaptive virtual machine (VM) migration to reduce communication costs in a virtualized environment. We introduce a new formal model for the problem of online VM migration in two scenarios: (1) VMs can be migrated arbitrarily in the substrate network; e.g., a private cloud provider may have an incentive to reduce the overall communication cost in the network. (2) VMs can only be migrated within a given tenant; e.g., a user that was assigned a set of physical machines may exchange the functionality of the VMs on these machines. We propose a simple class of Destination-Swap algorithms which are based on an aggressive collocation strategy (inspired by splay datastructures) and which maintain a minimal and local amount of per-node (amortized cost) information to decide where to migrate a VM and how; thus, the algorithms react quickly to changes in the load. The algorithms come in two main flavors, an indirect and distributed variant which keeps existing VM placements local, and a direct variant which keeps the number of affected VMs small. We show that naturally, inter-tenant optimizations yield a larger potential for optimization, but generally also a tenant itself can improve its embedding. Moreover, there exists an interesting tradeoff between direct and indirect strategies: indirect variants are preferable under skewed and sparse communication patterns due to their locality properties.

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preprint2013arXiv

The Constrained Virtual Steiner Arborescence Problem: Formal Definition, Single-Commodity Integer Programming Formulation and Computational Evaluation

As the Internet becomes more virtualized and software-defined, new functionality is introduced in the network core: the distributed resources available in ISP central offices, universal nodes, or datacenter middleboxes can be used to process (e.g., filter, aggregate or duplicate) data. Based on this new networking paradigm, we formulate the Constrained Virtual Steiner Arborescence Problem (CVSAP) which asks for optimal locations to perform In-network processing, in order to jointly minimize processing costs and network traffic while respecting link and node capacities. We prove that CVSAP cannot be approximated (unless P = NP), and accordingly, develop the exact algorithm VirtuCast to compute (near) optimal solutions. VirtuCast consists of: (1) a compact single-commodity flow Integer Programming (IP) formulation; (2) a flow decomposition algorithm to reconstruct individual routes from the IP solution. The compactness of the IP formulation allows for computing lower bounds even on large instances quickly, speeding up the algorithm. We rigorously prove VirtuCast's correctness. To complement our theoretical findings, we have implemented VirtuCast and present an extensive computational evaluation, showing that using VirtuCast realistically sized instances can be solved (close to) optimality. We show that VirtuCast significantly improves upon naive multi-commodity formulations and also initiate the study of primal heuristics to generate feasible solutions during the branch-and-bound process.

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preprint2012arXiv

A single ion as a three-body reaction center in an ultracold atomic gas

We report on three-body recombination of a single trapped Rb^+ ion and two neutral Rb atoms in an ultracold atom cloud. We observe that the corresponding rate coefficient K_3 depends on collision energy and is about a factor of 1000 larger than for three colliding neutral Rb atoms. In the three-body recombination process large energies up to several 0.1eV are released leading to an ejection of the ion from the atom cloud. It is sympathetically recooled back into the cloud via elastic binary collisions with cold atoms. Further, we find that the final ionic product of the three-body processes is again an atomic Rb^+ ion suggesting that the ion merely acts as a catalyzer, possibly in the formation of deeply bound Rb_2 molecules.

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preprint2012arXiv

An apparatus for immersing trapped ions into an ultracold gas of neutral atoms

We describe a hybrid vacuum system in which a single ion or a well defined small number of trapped ions (in our case Ba$^+$ or Rb$^+$) can be immersed into a cloud of ultracold neutral atoms (in our case Rb). This apparatus allows for the study of collisions and interactions between atoms and ions in the ultracold regime. Our setup is a combination of a Bose-Einstein condensation (BEC) apparatus and a linear Paul trap. The main design feature of the apparatus is to first separate the production locations for the ion and the ultracold atoms and then to bring the two species together. This scheme has advantages in terms of stability and available access to the region where the atom-ion collision experiments are carried out. The ion and the atoms are brought together using a moving 1-dimensional optical lattice transport which vertically lifts the atomic sample over a distance of 30$\,$cm from its production chamber into the center of the Paul trap in another chamber. We present techniques to detect and control the relative position between the ion and the atom cloud.

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preprint2012arXiv

Competitive and Deterministic Embeddings of Virtual Networks

Network virtualization is an important concept to overcome the ossification of today's Internet as it facilitates innovation also in the network core and as it promises a more efficient use of the given resources and infrastructure. Virtual networks (VNets) provide an abstraction of the physical network: multiple VNets may cohabit the same physical network, but can be based on completely different protocol stacks (also beyond IP). One of the main challenges in network virtualization is the efficient admission control and embedding of VNets. The demand for virtual networks (e.g., for a video conference) can be hard to predict, and once the request is accepted, the specification / QoS guarantees must be ensured throughout the VNet's lifetime. This requires an admission control algorithm which only selects high-benefit VNets in times of scarce resources, and an embedding algorithm which realizes the VNet in such a way that the likelihood that future requests can be embedded as well is maximized. This article describes a generic algorithm for the online VNet embedding problem which does not rely on any knowledge of the future VNet requests but whose performance is competitive to an optimal offline algorithm that has complete knowledge of the request sequence in advance: the so-called competitive ratio is, loosely speaking, logarithmic in the sum of the resources. Our algorithm is generic in the sense that it supports multiple traffic models, multiple routing models, and even allows for nonuniform benefits and durations of VNet requests.

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preprint2012arXiv

Generalized and Resource-Efficient VNet Embeddings with Migrations

This paper attends to the problem of embedding flexibly specified CloudNets, virtual networks connecting cloud resources (such as storage or computation). We attend to a scenario where customers can request CloudNets at short notice, and an infrastructure provider (or a potential itermediate broker or reseller) first embeds the CloudNet fast (e.g., using a simple heuristic). Later, however, long-lived CloudNets embeddings are optimized by migrating them to more suitable locations, whose precise definition depends on a given objective function. For instance, such migrations can be useful to reduce the peak resource loads in the network by spreading CloudNets across the infrastructure, to save energy by moving CloudNets together and switching off unused components, or for maintenance purposes. We present a very generic algorithm to compute optimal embeddings of CloudNets: It allows for different objective functions (such as load minimization or energy conservation), supports cost-aware migration, and can deal with all link types that arise in practice (e.g., full-duplex or even wireless or wired broadcast links with multiple endpoints). Our evaluation shows that such a rigorous optimization is even feasible in order to optimize a moderate-size CloudNet of full flexibility (e.g., a router site, a small physical infrastructure or virtual provider network).

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preprint2011arXiv

AntiJam: Efficient Medium Access despite Adaptive and Reactive Jamming

Intentional interference constitutes a major threat for communication networks operating over a shared medium where availability is imperative. Jamming attacks are often simple and cheap to implement. In particular, today's jammers can perform physical carrier sensing in order to disrupt communication more efficiently, specially in a network of simple wireless devices such as sensor nodes, which usually operate over a single frequency (or a limited frequency band) and which cannot benefit from the use of spread spectrum or other more advanced technologies. This article proposes the medium access (MAC) protocol \textsc{AntiJam} that is provably robust against a powerful reactive adversary who can jam a $(1-ε)$-portion of the time steps, where $ε$ is an arbitrary constant. The adversary uses carrier sensing to make informed decisions on when it is most harmful to disrupt communications; moreover, we allow the adversary to be adaptive and to have complete knowledge of the entire protocol history. Our MAC protocol is able to make efficient use of the non-jammed time periods and achieves an asymptotically optimal, $Θ{(1)}$-competitive throughput in this harsh scenario. In addition, \textsc{AntiJam} features a low convergence time and has good fairness properties. Our simulation results validate our theoretical results and also show that our algorithm manages to guarantee constant throughput where the 802.11 MAC protocol basically fails to deliver any packets.

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preprint2011arXiv

Misleading Stars: What Cannot Be Measured in the Internet?

Traceroute measurements are one of our main instruments to shed light onto the structure and properties of today's complex networks such as the Internet. This paper studies the feasibility and infeasibility of inferring the network topology given traceroute data from a worst-case perspective, i.e., without any probabilistic assumptions on, e.g., the nodes' degree distribution. We attend to a scenario where some of the routers are anonymous, and propose two fundamental axioms that model two basic assumptions on the traceroute data: (1) each trace corresponds to a real path in the network, and (2) the routing paths are at most a factor 1/alpha off the shortest paths, for some parameter alpha in (0,1]. In contrast to existing literature that focuses on the cardinality of the set of (often only minimal) inferrable topologies, we argue that a large number of possible topologies alone is often unproblematic, as long as the networks have a similar structure. We hence seek to characterize the set of topologies inferred with our axioms. We introduce the notion of star graphs whose colorings capture the differences among inferred topologies; it also allows us to construct inferred topologies explicitly. We find that in general, inferrable topologies can differ significantly in many important aspects, such as the nodes' distances or the number of triangles. These negative results are complemented by a discussion of a scenario where the trace set is best possible, i.e., "complete". It turns out that while some properties such as the node degrees are still hard to measure, a complete trace set can help to determine global properties such as the connectivity.

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preprint2011arXiv

On the Windfall and Price of Friendship: Inoculation Strategies on Social Networks

This article investigates selfish behavior in games where players are embedded in a social context. A framework is presented which allows us to measure the Windfall of Friendship, i.e., how much players benefit (compared to purely selfish environments) if they care about the welfare of their friends in the social network graph. As a case study, a virus inoculation game is examined. We analyze the corresponding Nash equilibria and show that the Windfall of Friendship can never be negative. However, we find that if the valuation of a friend is independent of the total number of friends, the social welfare may not increase monotonically with the extent to which players care for each other; intriguingly, in the corresponding scenario where the relative importance of a friend declines, the Windfall is monotonic again. This article also studies convergence of best-response sequences. It turns out that in social networks, convergence times are typically higher and hence constitute a price of friendship. While such phenomena may be known on an anecdotal level, our framework allows us to quantify these effects analytically. Our formal insights on the worst case equilibria are complemented by simulations shedding light onto the structure of other equilibria.

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preprint2011arXiv

Online Strategies for Intra and Inter Provider Service Migration in Virtual Networks

Network virtualization allows one to build dynamic distributed systems in which resources can be dynamically allocated at locations where they are most useful. In order to fully exploit the benefits of this new technology, protocols need to be devised which react efficiently to changes in the demand. This paper argues that the field of online algorithms and competitive analysis provides useful tools to deal with and reason about the uncertainty in the request dynamics, and to design algorithms with provable performance guarantees. As a case study, we describe a system (e.g., a gaming application) where network virtualization is used to support thin client applications for mobile devices to improve their QoS. By decoupling the service from the underlying resource infrastructure, it can be migrated closer to the current client locations while taking into account migration cost. This paper identifies the major cost factors in such a system, and formalizes the corresponding optimization problem. Both randomized and deterministic, gravity center based online algorithms are presented which achieve a good tradeoff between improved QoS and migration cost in the worst-case, both for service migration within an infrastructure provider as well as for networks supporting cross-provider migration. The paper reports on our simulation results and also presents an explicit construction of an optimal offline algorithm which allows, e.g., to evaluate the competitive ratio empirically.

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preprint2010arXiv

A Jamming-Resistant MAC Protocol for Multi-Hop Wireless Networks

This paper presents a simple local medium access control protocol, called \textsc{Jade}, for multi-hop wireless networks with a single channel that is provably robust against adaptive adversarial jamming. The wireless network is modeled as a unit disk graph on a set of nodes distributed arbitrarily in the plane. In addition to these nodes, there are adversarial jammers that know the protocol and its entire history and that are allowed to jam the wireless channel at any node for an arbitrary $(1-ε)$-fraction of the time steps, where $0<ε<1$ is an arbitrary constant. We assume that the nodes cannot distinguish between jammed transmissions and collisions of regular messages. Nevertheless, we show that \textsc{Jade} achieves an asymptotically optimal throughput if there is a sufficiently dense distribution of nodes.

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preprint2010arXiv

Dynamics of a cold trapped ion in a Bose-Einstein condensate

We investigate the interaction of a laser-cooled trapped ion (Ba$^+$ or Rb$^+$) with an optically confined $^{87}$Rb Bose-Einstein condensate (BEC). The system features interesting dynamics of the ion and the atom cloud as determined by their collisions and their motion in their respective traps. Elastic as well as inelastic processes are observed and their respective cross sections are determined. We demonstrate that a single ion can be used to probe the density profile of an ultracold atom cloud.

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preprint2010arXiv

On the Benefit of Virtualization: Strategies for Flexible Server Allocation

Virtualization technology facilitates a dynamic, demand-driven allocation and migration of servers. This paper studies how the flexibility offered by network virtualization can be used to improve Quality-of-Service parameters such as latency, while taking into account allocation costs. A generic use case is considered where both the overall demand issued for a certain service (for example, an SAP application in the cloud, or a gaming application) as well as the origins of the requests change over time (e.g., due to time zone effects or due to user mobility), and we present online and optimal offline strategies to compute the number and location of the servers implementing this service. These algorithms also allow us to study the fundamental benefits of dynamic resource allocation compared to static systems. Our simulation results confirm our expectations that the gain of flexible server allocation is particularly high in scenarios with moderate dynamics.

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preprint2010arXiv

Towards Network Games with Social Preferences

Many distributed systems can be modeled as network games: a collection of selfish players that communicate in order to maximize their individual utilities. The performance of such games can be evaluated through the costs of the system equilibria: the system states in which no player can increase her utility by unilaterally changing her behavior. However, assuming that all players are selfish and in particular that all players have the same utility function may not always be appropriate. Hence, several extensions to incorporate also altruistic and malicious behavior in addition to selfishness have been proposed over the last years. In this paper, we seek to go one step further and study arbitrary relationships between participants. In particular, we introduce the notion of the social range matrix and explore the effects of the social range matrix on the equilibria in a network game. In order to derive concrete results, we propose a simplistic network creation game that captures the effect of social relationships among players.

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