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International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 106439, 15 pages
http://dx.doi.org/10.1155/2012/106439
Research Article

An Energy-Efficient CKN Algorithm for Duty-Cycled Wireless Sensor Networks

1School of Software, Dalian University of Technology, Dalian 116621, China
2Department Multimedia Engineering, Osaka University, Osaka 565-0871, Japan
3School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China

Received 21 December 2011; Revised 14 March 2012; Accepted 15 March 2012

Academic Editor: Yunhao Liu

Copyright © 2012 Lei Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

To prolong the lifetime of a wireless sensor network, one common approach is to dynamically schedule sensors’ active/sleep cycles (i.e., duty cycles) using sleep scheduling algorithms. The connected K-neighborhood (CKN) algorithm is an efficient decentralized sleep scheduling algorithm for reducing the number of awake nodes while maintaining both network connectivity and an on-demand routing latency. In this paper, we investigate the unexplored energy consumption of the CKN algorithm by building a probabilistic node sleep model, which computes the probability that a random node goes to sleep. Based on this probabilistic model, we obtain a lower epoch bound that keeps the network more energy efficient with longer lifetime when it runs the CKN algorithm than it does not. Furthermore, we propose a new sleep scheduling algorithm, namely, Energy-consumption-based CKN (ECCKN), to prolong the network lifetime. The algorithm EC-CKN, which takes the nodes’ residual energy information as the parameter to decide whether a node to be active or sleep, not only can achieve the k-connected neighborhoods problem, but also can assure the k-awake neighbor nodes have more residual energy than other neighbor nodes in current epoch.