Asynchronous training in wireless sensor networks

Authors:
Ferruccio Barsi;Alan A. Bertossi;Francesco Betti Sorbelli;Roberto Ciotti;Stephan Olariu;Cristina M. Pinotti
Affiliations:
Department of Computer Science and Mathematics, University of Perugia, Perugia, Italy;Department of Computer Science, University of Bologna, Bologna, Italy;Department of Computer Science and Mathematics, University of Perugia, Perugia, Italy;Department of Computer Science and Mathematics, University of Perugia, Perugia, Italy;Department of Computer Science, Old Dominion University, Norfolk, VA;Department of Computer Science and Mathematics, University of Perugia, Perugia, Italy
Venue:
ALGOSENSORS'07 Proceedings of the 3rd international conference on Algorithmic aspects of wireless sensor networks
Year:
2007

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Abstract

A scalable energy-efficient training protocol is proposed for massively-deployed sensor networks, where sensors are initially anonymous and unaware of their location. The protocol is based on an intuitive coordinate system imposed onto the deployment area which partitions the anonymous sensors into clusters. The protocol is asynchronous, in the sense that the sensors wake up for the first time at random, then alternate between sleep and awake periods both of fixed length, and no explicit synchronization is performed between them and the sink. Theoretical properties are stated under which the training of all the sensors is possible. Moreover, a worst-case analysis as well as an experimental evaluation of the performance is presented, showing that the protocol is lightweight and flexible.