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Efficient Node Discovery in Mobile Wireless Sensor Networks

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Energy is one of the most crucial aspects in real deployments of mobile sensor networks. A large portion of the energy of sensor applications is spent in node discovery as nodes need to periodically advertise their presence and be awake to discover other nodes for data exchange. The optimization of energy consumption, which is generally a hard task in fixed sensor networks, is even harder in mobile sensor networks, where the neighbouring nodes change over time. In this paper we propose an algorithm for energy efficient node discovery in sparsely connected mobile wireless sensor networks. The work takes advantage of the fact that nodes have temporal patterns of encounters and exploits these patterns to drive the duty cycling. We have used reinforcement learning techniques to detect and dynamically change the times at which a node should be awake as it is likely to encounter other nodes. We have evaluated our work using real human mobility traces, and the paper presents the performance of the protocol in this context.

Bio: Vladimir Dyo is a PhD candidate at University College London working under supervision of Dr. Cecilia Mascolo. He obtained his MSc in Data Communications, Networks and Distributed Systems from UCL in 2003 and a BSc in Computer Engineering from Kazakh National Technical University in 1998. His interests include: mobile wireless sensor networks, their applications for wildlife tracking, duty cycling and MAC protocols for sensor networks.

This talk is part of the Computer Laboratory Systems Research Group Seminar series.

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