Fairness in Multiterminal Data Compression: A Splitting Method for the Egalitarian Solution

Ni Ding, David Smith, Parastoo Sadeghi, Thierry Rakotoarivelo

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    This paper proposes a novel splitting (SPLIT) algorithm to achieve fairness in the multiterminal lossless data compression problem. It finds the egalitarian solution in the Slepian-Wolf region and completes in strongly polynomial time. We show that the SPLIT algorithm adaptively updates the source coding rates to the optimal solution, while recursively splitting the terminal set, enabling parallel and distributed computation. The result of an experiment demonstrates a significant reduction in computation time by the parallel implementation when the number of terminals becomes large. The achieved egalitarian solution is also shown to be superior to the Shapley value in distributed networks, e.g., wireless sensor networks, in that it best balances the nodes' energy consumption and is far less computationally complex to obtain.

    Original languageEnglish
    Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages6383-6387
    Number of pages5
    ISBN (Print)9781538646588
    DOIs
    Publication statusPublished - 10 Sept 2018
    Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
    Duration: 15 Apr 201820 Apr 2018

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume2018-April
    ISSN (Print)1520-6149

    Conference

    Conference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
    Country/TerritoryCanada
    CityCalgary
    Period15/04/1820/04/18

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