A Bayesian network approach to a biologically inspired motion strategy for mobile wireless sensor networks

Matthew Coles, Djamel Azzi, B. Haynes, Alan Hewitt

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Mobility strategies for wireless sensor networks (WSNs) are presented. We introduce a grazing mobility strategy for mobile WSNs, inspired by the foraging behaviour of herbivores grazing pastures. We present Bayesian network GRAZing (BNGRAZ) that implements the proposed WSN grazing strategy. BNGRAZ uses local neighbourhood information to predict coverage and connectivity performance changes related to sensor node motion characteristics. This enables a sensor node to predict the performance implications related to its direction of movement. We implement the BNGRAZ approach to grazing in a custom built mobile WSN simulator. The WSN performance criteria considered during the validation process include coverage, redundancy, connectivity, and network lifetime.
    Original languageEnglish
    Pages (from-to)1217-1228
    Number of pages12
    JournalAd Hoc Networks
    Volume7
    Issue number6
    DOIs
    Publication statusPublished - 2009

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