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Improving of entropy adaptive on-line compression

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Abstract

Since energy efficiency, high bandwidth, and low transmission delay are challenging issues in mobile networks, due to resource constraints, there is a great importance in designing of new communication methods. In particular, lossless data compression may provide high performance under constrained resources. In this paper we present a novel on-line and entropy adaptive compression scheme for streaming unbounded length inputs. The scheme extends the window dictionary Lempel–Ziv compression and is adaptive and tailored to compress on-line non entropy stationary inputs. Specifically, the window dictionary size is changed in an adaptive manner to fit the current best compression rate for the input. On-line entropy adaptive compression scheme (EAC), introduced and analyzed in this paper, examines all possible sliding window sizes over the next input portion to choose the optimal window size for this portion; a size that implies the best compression ratio. The size found is then used in the actual compression of this portion. We suggest an adaptive encoding scheme, which optimizes the parameters block by block, and base the compression performance on the optimality proof of LZ77 when applied to blocks (Ziv in IEEE Trans Inf Theory 55(5):1941–1944, 2009). This adaptivity can be useful for many communication tasks. In particular, providing efficient utilization of energy consuming wireless devices by data compression. Due to the dynamic and non-uniform structure of multimedia data, adaptive approaches for data processing are of special interest. The EAC scheme was tested on different types of files (docx, ppt, jpeg, xls) and over synthesized files that were generated as segments of homogeneous Markov Chains. Our experiments demonstrate that the EAC scheme typically provides a higher compression ratio than LZ77 does, when examined in the scope of on-line per-block compression of transmitted (or compressed) files. We propose techniques intended to control the adaptive on-line compression process by estimating relative entropy between two sequential blocks of data. This approach may enhance performance of the mobile networks.

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Acknowledgments

We thank Asaf Cohen for useful remarks and discussions. We thank Dmitry Zbarski for implementing and testing our Entropy Adaptive Compression scheme. We thank the Editor and the manuscript reviewers for their invaluable suggestions and comments.

Author information

Authors and Affiliations

  1. Department of Computer Science, Ben-Gurion University of the Negev, 84105, Beer-Sheva, Israel

    Shlomi Dolev & Muni Venkateswarlu Kumaramangalam

  2. Institute of Informatics Problems of Federal Research Center “Computer Science and Control” of Russian Academy of Sciences, Moscow, Russia

    Sergey Frenkel

  3. Department of Software Engineering, Sami-Shamoon College of Engineering, 84100, Beer-Sheva, Israel

    Marina Kopeetsky

Authors
  1. Shlomi Dolev
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  2. Sergey Frenkel
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  3. Marina Kopeetsky
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  4. Muni Venkateswarlu Kumaramangalam
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Corresponding author

Correspondence to Marina Kopeetsky.

Additional information

Partially supported by Deutsche Telekom, Rita Altura Trust Chair in Computer Sciences, Israeli Internet Association, Israeli Ministry of Science, Lynne and William Frankel Center and Israel Science Foundation (Grant number 428/11). The second author has been partially supported by the Russian Foundation for Basic Research under grant RFBR 15-07-05316. The third author has been partially supported by the internal research program of the Shamoon College of Engineering. An extended abstract of this work was presented at IEEE NCA 2014.

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Dolev, S., Frenkel, S., Kopeetsky, M. et al. Improving of entropy adaptive on-line compression. Wireless Netw 23, 2521–2532 (2017). https://doi.org/10.1007/s11276-016-1289-9

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  • DOI: https://doi.org/10.1007/s11276-016-1289-9

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