Name
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1155/2012/106439 | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS |
Field | DocType | Volume |
Network connectivity,Computer science,Scheduling (computing),Latency (engineering),Computer network,Real-time computing,Probabilistic logic,Distributed computing,Efficient energy use,Algorithm,Statistical model,Energy consumption,Wireless sensor network | Journal | 2012 |
Issue | ISSN | Citations |
null | 1550-1477 | 8 |
PageRank | References | Authors |
0.64 | 22 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Wang | 1 | 433 | 64.21 |
| Zhuxiu Yuan | 2 | 61 | 7.20 |
| Shu Lei | 3 | 2927 | 216.78 |
| Liang Shi | 4 | 87 | 10.21 |
| Zhenquan Qin | 5 | 76 | 14.43 |