QoI-aware energy-efficient participatory crowdsourcing

Chi Harold Liu, Jun Fan, Pan Hui, Jon Crowcroft, Gangyi Ding

    Research output: Contribution to journalArticleScientificpeer-review

    10 Citations (Scopus)

    Abstract

    Today's smartphones not only serve as a means of personal communication device, but are also fundamentally transforming the traditional understanding of crowdsourcing to an emerging type of participatory, task-oriented applications. It aims to support the so-called Citizen Science efforts for knowledge discovery, to understand the human behavior and measure/evaluate their opinions. In this paper, to facilitate the above scenarios, we propose a novel energy-efficient participatory crowdsourcing framework that meets the quality-of-information (QoI) requirements of the request in a distributed manner. Specifically, we extend the traditional framework of Gur Game for distributed decision-making to recommend the level of information contribution for each participant, by merging the multiple automaton chains into a single chain with multiple steady states. We evaluate the proposed scheme under the MIT social evolution data set, where the QoI requirements of the request are successfully achieved, with a satisfactory level of energy consumption fairness among participants, of negligible computational complexity. Finally, we explore the impact of community structure on the proposed algorithm, and propose a feasible method to facilitate the local data aggregation.

    Original languageEnglish
    Article number6522522
    Pages (from-to)3742-3753
    Number of pages12
    JournalIEEE Sensors Journal
    Volume13
    Issue number10
    DOIs
    Publication statusPublished - 2013
    MoE publication typeA1 Journal article-refereed

    Keywords

    • energy efficiency
    • gur Game
    • Participatory crowdsourcing
    • quality-of-information

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