Name
Abstract | ||
|---|---|---|
Sensor networks consist of autonomous nodes with battery powered. Nodes can be sleep to extend the lifetime of network without compromising area coverage and network connectivity. Most existing approaches to connected coverage require knowledge of accurate location information. However, the energy cost and system complexity involved in obtaining the accurate location information may compromise the effectiveness of proposed solution as a whole. This paper addresses the problem of maximizing network lifetime while providing coverage and connectivity without accurate location information of sensor nodes. Our solution is based on the theoretical analysis of the sensing area coverage property of minimal dominating set. We establish the relationship between point coverage and area coverage in random geometric graphs. Based on the analytical results and Rule K algorithms constructing the connected dominating set, a Location-Unaware Connected Coverage Protocol (LUCCP) is proposed. Simulation studies show that the proposed LUCCP can effectively maintain both high quality sensing coverage and connectivity for a long time. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-73549-6_52 | UIC |
Keywords | Field | DocType |
proposed solution,location-unaware connected coverage protocol,wireless sensor network,network connectivity,proposed luccp,sensor network,network lifetime,connected coverage,point coverage,accurate location information,area coverage property,area coverage,dominating set,random geometric graph,connected dominating set | Network connectivity,Graph,Key distribution in wireless sensor networks,Dominating set,Computer science,Computer network,Connected dominating set,Battery (electricity),Wireless sensor network,Distributed computing,Area coverage | Conference |
Volume | ISSN | ISBN |
4611 | 0302-9743 | 3-540-73548-8 |
Citations | PageRank | References |
0 | 0.34 | 12 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingchi Mao | 1 | 40 | 8.61 |
| Lijun Chen | 2 | 181 | 20.57 |
| Daoxu Chen | 3 | 745 | 62.01 |