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Researcher profile

Samarjit Chakraborty

Samarjit Chakraborty contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Networking and Internet Architectureeess.SPDistributed, Parallel, and Cluster Computingeess.SYgr-qchep-thMachine LearningSystems and ControlArtificial IntelligenceComputer Visioncs.CYInformation Theorymath.ITphysics.gen-phPopulations and Evolution

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Published work

13 published item(s)

preprint2026arXiv

Autonomous Systems Dependability in the era of AI: Design Challenges in Safety, Security, Reliability and Certification

The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of intelligent, data-driven components. Ensuring dependability in such systems requires a holistic approach that spans multiple abstraction layers and encompasses both design- and run-time assurance. Traditional methods for reliability, safety, and security management often fall short in addressing the dynamic and uncertain behaviors introduced by Artificial Intelligence (AI) and Machine Learning (ML) components, especially under stringent real-time, power, and safety constraints. While AI and ML offer powerful predictive, adaptive, and self-optimizing capabilities that can enhance system dependability, their inherent non-determinism, data-dependence, and lack of formal guarantees introduce new challenges for verification, validation, and certification. This paper explores emerging methodologies, architectures, and frameworks for designing dependable autonomous and embedded systems in the era of AI. It highlight advances in reliability modeling, secure system design, and certification approaches that account for imperfect, learning-enabled components, aiming to bridge the gap between AI innovation and certifiable system-level dependability.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Resource-Conscious RL Algorithms for Deep Brain Stimulation

Deep Brain Stimulation (DBS) has proven to be a promising treatment of Parkinson's Disease (PD). DBS involves stimulating specific regions of the brain's Basal Ganglia (BG) using electric impulses to alleviate symptoms of PD such as tremors, rigidity, and bradykinesia. Although most clinical DBS approaches today use a fixed frequency and amplitude, they suffer from side effects (such as slurring of speech) and shortened battery life of the implant. Reinforcement learning (RL) approaches have been used in recent research to perform DBS in a more adaptive manner to improve overall patient outcome. These RL algorithms are, however, too complex to be trained in vivo due to their long convergence time and requirement of high computational resources. We propose a new Time & Threshold-Triggered Multi-Armed Bandit (T3P MAB) RL approach for DBS that is more effective than existing algorithms. Further, our T3P agent is lightweight enough to be deployed in the implant, unlike current deep-RL strategies, and even forgoes the need for an offline training phase. Additionally, most existing RL approaches have focused on modulating only frequency or amplitude, and the possibility of tuning them together remains greatly unexplored in the literature. Our RL agent can tune both frequency and amplitude of DBS signals to the brain with better sample efficiency and requires minimal time to converge. We implement an MAB agent for DBS for the first time on hardware to report energy measurements and prove its suitability for resource-constrained platforms. Our T3P MAB algorithm is deployed on a variety of microcontroller unit (MCU) setups to show its efficiency in terms of power consumption as opposed to other existing RL approaches used in recent work.

0 citations0 reviewsNo code linkedOpen access
preprint2024arXiv

To Balance or to Not? Battery Aging-Aware Active Cell Balancing for Electric Vehicles

Due to manufacturing variabilities and temperature gradients within an electric vehicle's battery pack, the capacities of cells in it decrease differently over time. This reduces the usable capacity of the battery - the charge levels of one or more cells might be at the minimum threshold while most of the other cells have residual charge. Active cell balancing (i.e., transferring charge among cells) can equalize their charge levels, thereby increasing the battery pack's usable capacity. But performing balancing means additional charge transfer, which can result in energy loss and cell aging, akin to memory aging in storage technologies due to writing. This paper studies when cell balancing should be optimally triggered to minimize aging while maintaining the necessary driving capability. In particular, we propose optimization strategies for cell balancing while minimizing their impact on aging. By borrowing terminology from the storage domain, we refer to this as "wear leveling-aware" active balancing.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

How appropriate are the gravitational entropy proposals for traversable wormholes?

In this paper we have examined the validity of some proposed definitions of gravitational entropy (GE) in the context of traversable wormhole solutions of the Einstein field equations. Here we have adopted two different proposals of GE and checked for their applicability in the case of these wormholes. The first one is the phenomenological approach proposed by Rudjord et al \cite{entropy1} and expanded by Romero et al in \cite{entropy2}, which is a purely geometric method of measuring gravitational entropy. The latter one is the Clifton-Ellis-Tavakol (CET) proposal \cite{CET} for the gravitational entropy which arises in relativistic thermodynamics and is based on the Bel-Robinson tensor, which represents the effective super-energy-momentum tensor of free gravitational fields. Considering some of the Lorentzian traversable wormholes along with the Brill solution for NUT wormholes and the AdS wormholes, we have evaluated the gravitational entropy for these systems. Incidentally, the application of the CET proposal can provide unique gravitational entropies for spacetimes of Petrov type D and N only, whereas the geometric method can be applied to almost every kind of spacetime, although it has no relation with thermodynamics. For any traversable wormhole to be physically realistic, it should have a viable GE. We found that the GE proposals do give us a consistent measure of GE in several of them. This means that the existence of a viable gravitational entropy strictly depends on its definition.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

WiFiEye -- Seeing over WiFi Made Accessible

While commonly used for communication purposes, an increasing number of recent studies consider WiFi for sensing. In particular, wireless signals are altered (e.g., reflected and attenuated) by the human body and objects in the environment. This can be perceived by an observer to infer information on human activities or changes in the environment and, hence, to "see" over WiFi. Until now, works on WiFi-based sensing have resulted in a set of custom software tools - each designed for a specific purpose. Moreover, given how scattered the literature is, it is difficult to even identify all steps/functions necessary to build a basic system for WiFi-based sensing. This has led to a high entry barrier, hindering further research in this area. There has been no effort to integrate these tools or to build a general software framework that can serve as the basis for further research, e.g., on using machine learning to interpret the altered WiFi signals. To address this issue, in this paper, we propose WiFiEye - a generic software framework that makes all necessary steps/functions available "out of the box". This way, WiFiEye allows researchers to easily bootstrap new WiFi-based sensing applications, thereby, focusing on research rather than on implementation aspects. To illustrate WiFiEye's workflow, we present a case study on WiFi-based human activity recognition.

0 citations0 reviewsNo code linkedOpen access
preprint2021arXiv

Performance Limits of Neighbor Discovery in Wireless Networks

Neighbor Discovery (ND) is the process employed by two wireless devices to discover each other. There are many different ND protocols, both in the scientific literature and also those employed in practice. All ND protocols involve devices sending beacons, and also listening for them. Protocols differ in terms of how the beacon transmissions and reception windows are scheduled, and the device sleeps in between consecutive transmissions and reception windows in order to save energy. A successful discovery constitutes a sending device's beacon overlapping with a receiving device's reception window. The goal of all ND protocols is to minimize the discovery latency. In spite of the ubiquity of ND protocols and active research on this topic for over two decades, the basic question "Given an energy budget, what is the minimum guaranteed ND latency?", however, still remains unanswered. Given the different kinds of protocols that exist, there has also been no standard way of comparing them and their performance. This paper, for the first time, answers the question on the best-achievable ND latency for a given energy budget. We derive discovery latencies for different scenarios, e.g., when both devices have the same energy budgets, and both devices have different energy budgets. We also show that some existing protocols can be parametrized such that they perform optimally. The fact that the parametrizations of some other protocols were optimal was not known before, and can now be established using our technique. Our results are restricted to the case when a few devices discover each other at a time, as is the case in most real-life scenarios. When many devices need to discover each other simultaneously, packet collisions play a dominant role in the discovery latency and how to analyze such scenarios need further study.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

How Reliable is Smartphone-based Electronic Contact Tracing for COVID-19?

Smartphone-based electronic contact tracing is currently considered an essential tool towards easing lockdowns, curfews, and shelter-in-place orders issued by most governments around the world in response to the 2020 novel coronavirus (SARS-CoV-2) crisis. While the focus on developing smartphone-based contact tracing applications or apps has been on privacy concerns stemming from the use of such apps, an important question that has not received sufficient attention is: How reliable will such smartphone-based electronic contact tracing be? This is a technical question related to how two smartphones reliably register their mutual proximity. Here, we examine in detail the technical prerequisites required for effective smartphone-based contact tracing. The underlying mechanism that any contact tracing app relies on is called Neighbor Discovery (ND), which involves smartphones transmitting and scanning for Bluetooth signals to record their mutual presence whenever they are in close proximity. The hardware support and the software protocols used for ND in smartphones, however, were not designed for reliable contact tracing. In this paper, we quantitatively evaluate how reliably can smartphones do contact tracing. Our results point towards the design of a wearable solution for contact tracing that can overcome the shortcomings of a smartphone-based solution to provide more reliable and accurate contact tracing. To the best of our knowledge, this is the first study that quantifies, both, the suitability and also the drawbacks of smartphone-based contact tracing. Further, our results can be used to parameterize a ND protocol to maximize the reliability of any contact tracing app that uses it.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Optimizing BLE-Like Neighbor Discovery

Neighbor discovery (ND) protocols are used for establishing a first contact between multiple wireless devices. The energy consumption and discovery latency of this procedure are determined by the parametrization of the protocol. In most existing protocols, reception and transmission are temporally coupled. Such schemes are referred to as \textit{slotted}, for which the problem of finding optimized parametrizations has been studied thoroughly in the literature. However, slotted approaches are not efficient in applications in which new devices join the network gradually and only the joining devices and a master node need to run the ND protocol simultaneously. For example, this is typically the case in IoT scenarios or Bluetooth Low Energy (BLE) piconets. Here, protocols in which packets are transmitted with periodic intervals (PI) can achieve significantly lower worst-case latencies than slotted ones. For this class of protocols, optimal parameter values remain unknown. To address this, we propose an optimization framework for PI-based BLE-like protocols, which translates any specified duty-cycle (and therefore energy budget) into a set of optimized parameter values. We show that the parametrizations resulting from one variant of our proposed scheme are optimal when one receiver discovers one transmitter, and no other parametrization or ND protocol - neither slotted nor slotless - can guarantee lower discovery latencies for a given duty-cycle in this scenario. Since the resulting protocol utilizes the channel more aggressively than other ND protocols, beacons will collide more frequently. Hence, due to collisions, the rate of successful discoveries gracefully decreases for larger numbers of devices discovering each other simultaneously. We also propose a scheme for configuring the BLE protocol (and not just BLE-\textit{like} protocols).

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

The Time-Triggered Wireless Architecture

Wirelessly interconnected sensors, actuators, and controllers promise greater flexibility, lower installation and maintenance costs, and higher robustness in harsh conditions than wired solutions. However, to facilitate the adoption of wireless communication in cyber-physical systems (CPS), the functional and non-functional properties must be similar to those known from wired architectures. We thus present Time-Triggered Wireless (TTW), a wireless architecture for multi-mode CPS that offers reliable communication with guarantees on end-to-end delays among distributed applications executing on low-cost, low-power embedded devices. We achieve this by exploiting the high reliability and deterministic behavior of a synchronous transmission based communication stack we design, and by coupling the timings of distributed task executions and message exchanges across the wireless network by solving a novel co-scheduling problem. While some of the concepts in TTW have existed for some time and TTW has already been successfully applied for feedback control and coordination of multiple mechanical systems with closed-loop stability guarantees, this paper presents the key algorithmic, scheduling, and networking mechanisms behind TTW, along with their experimental evaluation, which have not been known so far. TTW is open source and ready to use: ttw.ethz.ch

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Unsupervised and Supervised Learning with the Random Forest Algorithm for Traffic Scenario Clustering and Classification

The goal of this paper is to provide a method, which is able to find categories of traffic scenarios automatically. The architecture consists of three main components: A microscopic traffic simulation, a clustering technique and a classification technique for the operational phase. The developed simulation tool models each vehicle separately, while maintaining the dependencies between each other. The clustering approach consists of a modified unsupervised Random Forest algorithm to find a data adaptive similarity measure between all scenarios. As part of this, the path proximity, a novel technique to determine a similarity based on the Random Forest algorithm is presented. In the second part of the clustering, the similarities are used to define a set of clusters. In the third part, a Random Forest classifier is trained using the defined clusters for the operational phase. A thresholding technique is described to ensure a certain confidence level for the class assignment. The method is applied for highway scenarios. The results show that the proposed method is an excellent approach to automatically categorize traffic scenarios, which is particularly relevant for testing autonomous vehicle functionality.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

Vehicle Position Estimation with Aerial Imagery from Unmanned Aerial Vehicles

The availability of real-world data is a key element for novel developments in the fields of automotive and traffic research. Aerial imagery has the major advantage of recording multiple objects simultaneously and overcomes limitations such as occlusions. However, there are only few data sets available. This work describes a process to estimate a precise vehicle position from aerial imagery. A robust object detection is crucial for reliable results, hence the state-of-the-art deep neural network Mask-RCNN is applied for that purpose. Two training data sets are employed: The first one is optimized for detecting the test vehicle, while the second one consists of randomly selected images recorded on public roads. To reduce errors, several aspects are accounted for, such as the drone movement and the perspective projection from a photograph. The estimated position is comapared with a reference system installed in the test vehicle. It is shown, that a mean accuracy of 20 cm can be achieved with flight altitudes up to 100 m, Full-HD resolution and a frame-by-frame detection. A reliable position estimation is the basis for further data processing, such as obtaining additional vehicle state variables. The source code, training weights, labeled data and example videos are made publicly available. This supports researchers to create new traffic data sets with specific local conditions.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

On the gravitational entropy of accelerating black holes

In this paper we have examined the validity of a proposed definition of gravitational entropy in the context of accelerating black hole solutions of the Einstein field equations, which represent the realistic black hole solutions. We have adopted a phenomenological approach proposed in Rudjord et al [20] and expanded by Romero et al [21], in which the Weyl curvature hypothesis is tested against the expressions for the gravitational entropy. Considering the $C$-metric for the accelerating black holes, we have evaluated the gravitational entropy and the corresponding entropy density for four different types of black holes, namely, non-rotating black hole, non-rotating charged black hole, rotating black hole and rotating charged black hole. We end up by discussing the merits of such an analysis and the possible reason of failure in the particular case of rotating charged black hole and comment on the possible resolution of the problem.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Thermodynamics of FRW Universe With Chaplygin Gas Models

In this paper we have examined the validity of the generalized second law of thermodynamics (GSLT) in an expanding Friedmann Robertson Walker (FRW) universe filled with different variants of Chaplygin gases. Assuming that the universe is a closed system bounded by the cosmological horizon, we first present the general prescription for the rate of change of total entropy on the boundary. In the subsequent part we have analyzed the validity of the generalised second law of thermodynamics on the cosmological apparent horizon and the cosmological event horizon for different Chaplygin gas models of the universe. The analysis is supported with the help of suitable graphs to clarify the status of the GSLT on the cosmological horizons. In the case of the cosmological apparent horizon we have found that some of these models always obey the GSLT, whereas the validity of GSLT on the cosmological event horizon of all these models depend on the choice of free parameters in the respective models.

0 citations0 reviewsNo code linkedOpen access