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Bicriteria data compression

The advent of massive datasets (and the consequent design of high-performing distributed storage systems) have reignited the interest of the scientific and engineering community towards the design of lossless data compressors which achieve effective compression ratio and very efficient decompression speed. Lempel-Ziv's LZ77 algorithm is the de facto choice in this scenario because of its decompression speed and its flexibility in trading decompression speed versus compressed-space efficiency. Each of the existing implementations offers a trade-off between space occupancy and decompression speed, so software engineers have to content themselves by picking the one which comes closer to the requirements of the application in their hands. Starting from these premises, and for the first time in the literature, we address in this paper the problem of trading optimally, and in a principled way, the consumption of these two resources by introducing the Bicriteria LZ77-Parsing problem, which formalizes in a principled way what data-compressors have traditionally approached by means of heuristics. The goal is to determine an LZ77 parsing which minimizes the space occupancy in bits of the