A self-adaptive MAC protocol for supporting mobile nodes in wireless sensor networks (Self-MACm)

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Several applications have been proposed for wireless sensor networks. Some of them, such as the ones proposed for supervising the rehabilitation of patients, require mobile nodes. But mobility brings with it several challenges. This project will address two of them, namely, (1) the need to reduce the latency of establishing new links and (2) the need to adapt the duty cycle of static nodes to support an energy-efficient and a quality-of-service-aware multi-hop communication. For both challenges, we propose to adopt Bayesian Estimation approach to model and reason about the deterioration rate of a link quality between a mobile and a static node and the packet arrival and departure rates of relay nodes. Thus, we model link quality deterioration and packet reception rate as random processes and dynamically update their probability density functions at runtime by analysing the quality of received packets. We then employ the density functions to predict future link quality and packet arrival rate. The prediction will then serve to carry out a seamless handover and to dynamically and asynchronously adapt the duty cycle of relay nodes.