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