Evolutionary coalitional game for correlation-aware clustering in machine-to-machine communications

Nicole Sawyer, Mehdi Naderi Soorki, Walid Saad, David B. Smith

    Research output: Contribution to journalConference articlepeer-review

    4 Citations (Scopus)

    Abstract

    In this paper, the problem of correlation-aware clustering is studied for a dense network of machine-type devices (MTDs) deployed over a cellular network. In such dense networks, MTDs sense an environment and transmit their data to the base station (BS) via a cellular uplink. However, since MTDs are typically closely located to each other they will gather correlated data, and, thus, large amounts of redundant bits can be transmitted to the BS. To address this problem, an evolutionary coalitional (EC) game is proposed to cluster MTDs into coalitions in a fully distributed and autonomous manner, based on the correlation of their data. The proposed EC game allows a reduction in the number of redundant bits being sent to the BS, while also reducing the energy used for transmission by each MTD. To solve the EC game, a distributed coalition formation algorithm is proposed and shown to reach an evolutionary stable coalition structure, which is robust to a small portion of MTDs changing their strategy at the stable outcome. For this game, the maximum portion of MTDs that can deviate from the stable coalitional structure is derived. Simulation results show that the proposed approach can effectively cluster MTDs with highly correlated data which, in turn, enables those MTDs to eliminate a large number of redundant bits. Moreover, the results show that, for a given maximum correlation factor and network density, the transmission energy per MTD can be decreased by 19%, compared to a baseline merge-and-split algorithm. In addition, when a maximum correlation factor is considered, the number of redundant bits that can be eliminated per coalition is increased by 50%, compared to the merge-and-split algorithm.

    Original languageEnglish
    Pages (from-to)1-6
    Number of pages6
    JournalProceedings - IEEE Global Communications Conference, GLOBECOM
    Volume2018-January
    DOIs
    Publication statusPublished - 2017
    Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
    Duration: 4 Dec 20178 Dec 2017

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