科研之友
微信
新浪微博
Facebook
分享链接
摘要
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.
