Game Theoretic Approach Towards Energy - Efficient Task Distribution in Multitasking Wireless Sensor Networks

Mo Haghighi, Konstantinos Maraslis, Theo Tryfonas, George Oikonomou

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

4 Citations (Scopus)

Abstract

WSNs have a wide variety of applications, and their usability for remote monitoring of various parameters of interest is growing dramatically. Conventional applications mostly involved a single WSN for collecting raw parameters with limited aggregation on the node side, whereby more sophisticated data mining was implemented by the end-users. Recent applications however, often require more intelligent functions, in which nodes are expected to implement logical decision-makings on the aggregated data. Implementing such functions often involves more processing, and wider interactions amongst network peers, hence resulting in higher energy consumption and shorter node lifetime. Sensomax is an agent-based WSN middleware, which facilitates seamless integration of mathematical functions in large-scale wireless sensor networks. In this paper, we will investigate game theoretic and auction-based techniques in order to optimise task distribution and energy consumption in WSNs.
Original languageEnglish
Title of host publicationIEEE Sensors 2015
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-4
DOIs
Publication statusPublished - Nov 2015
EventIEEE Sensors 2015 - Busan Exhibition and Convention Center, Busan, Korea, Republic of
Duration: 1 Nov 20154 Nov 2015

Conference

ConferenceIEEE Sensors 2015
CountryKorea, Republic of
CityBusan
Period1/11/154/11/15

Structured keywords

  • Digital Health

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  • Projects

    SPHERE (EPSRC IRC)

    Craddock, I. J., Coyle, D. T., Flach, P. A., Kaleshi, D., Mirmehdi, M., Piechocki, R. J., Stark, B. H., Ascione, R., Ashburn, A. M., Burnett, M. E., Damen, D., Gooberman-Hill, R. J. S., Harwin, W. S., Hilton, G., Holderbaum, W., Holley, A. P., Manchester, V. A., Meller, B. J., Stack, E. & Gilchrist, I. D.

    1/10/1330/09/18

    Project: Research, Parent

    Cite this

    Haghighi, M., Maraslis, K., Tryfonas, T., & Oikonomou, G. (2015). Game Theoretic Approach Towards Energy - Efficient Task Distribution in Multitasking Wireless Sensor Networks. In IEEE Sensors 2015 (pp. 1-4). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICSENS.2015.7370652