Lifetime Optimization for Wireless Sensor Networks with Correlated Data Gathering

Abstract : The nodes in wireless sensor networks often collect correlated measurements. Not taking into account this information redundancy is detrimental to the network lifetime, since communication is often the most energy consuming task for a sensor node. This paper tackles this issue by proposing an approach based on Distributed Source Coding (DSC), in which the rate assignments are adapted over time. The distinctive feature of the DSC technique is to make the compression independent of the routing. We rely on this feature to design two algorithms applicable to multi-hop routing trees to optimize the network lifetime. The first algorithm is the Updated CMAX (UCMAX) which improves the centralized CMAX routing algorithm, by considering the energy loss due to packet forwarding in multi-hop networks. The second algorithm is called Adaptive Compression Rate (ACR), and aims at maximizing the network lifetime by better balancing the energy losses in the network. Experimental results show that the proposed approach is easy to tune, and may significantly extend the network lifetime, particularly for dense, multi-hop networks.
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WiOpt'10: Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, May 2010, Avignon, France. pp.252-258, 2010
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Nashat Abughalieh, Yann-Aël Le Borgne, Kris Steenhaut, Ann Nowé. Lifetime Optimization for Wireless Sensor Networks with Correlated Data Gathering. WiOpt'10: Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, May 2010, Avignon, France. pp.252-258, 2010. 〈inria-00503914〉

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