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Energy-efficient node position identification through payoff matrix and variability analysis

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Abstract

Applications for mobile ad-hoc networks are heavily dependent on information about the nodes positions. Since the network may include malicious nodes providing bogus data (e.g., fake positions), the reliability of this information is critical. Although this problem has been addressed by some predictive models, challenges still exist regarding (a) the accuracy/security of such models, (b) the potential advantages of combining different prediction models, (c) the power consumption resulting from the simultaneous application of multiple models, and (d) the lack of strategic approaches in the analysis of information aiming to find the most advantageous data and balance divergent results. To address these issues, we analyze in this paper the performance of two prediction methods: linear regression and Grey model. We have evaluated their corresponding energy costs for reliably identifying each node position. The results, obtained via simulations, are added to independent vectors and statistical indicators are gathered to create a game theory payoff matrix. The proposed model allows the evaluation of the predictive methods either individually or collectively, facilitating the identification of the best parameters for a target energy saving profile.

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Notes

  1. http://www.ulb.ac.be/di/labo/datasets.html.

  2. http://www.moteiv.com.

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Author information

Authors and Affiliations

  1. CERI-LIA (Computer Science Laboratory) at the University of Avignon, Avignon, France

    Fen Zhou

  2. Polytechnical School Universidade de Sao Paulo, Universidade Paulista (UNIP) and Instituto de Pesquisas Tecnologicas (IPT), São Paulo, Brazil

    Anderson Silva

  3. Polytechnical School LSI/LARC-USP, Universidade de Sao Paulo, São Paulo, Brazil

    Elvis Pontes, Marcos A. Simplicio & Sergio Kofuji

  4. PIT, Universidade de Aveiro, Aveiro, Portugal

    Rui Aguiar

  5. Universidade do Oeste Paulista (FIPP) and Instituto de Pesquisas Tecnologicas (IPT), São Paulo, Brazil

    Adilson Guelfi

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  1. Anderson Silva
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  2. Fen Zhou
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  3. Elvis Pontes
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  4. Marcos A. Simplicio
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Corresponding author

Correspondence to Fen Zhou.

Additional information

Part of this work has been presented at IEEE GLOBECOM 2014 and published in its proceedings [42].

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Silva, A., Zhou, F., Pontes, E. et al. Energy-efficient node position identification through payoff matrix and variability analysis. Telecommun Syst 65, 459–477 (2017). https://doi.org/10.1007/s11235-016-0245-4

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