Name
Abstract | ||
|---|---|---|
A crucial issue in the management of sensor networks is the continuous monitoring of residual energy level of the sensors in the network. With the large number of sensors in a typical network, the energy monitoring process can itself be very energy intensive. In this article, we propose a hierarchical approach to construct a continuous energy map of a sensor network. Our method consists of a topology discovery and clustering phase, followed by an aggregation phase when energy information collected is abstracted and merged into energy contours in which nodes with similar energy level are grouped into the same region. The topology of the monitoring tree is restructured periodically to distribute energy cost among all nodes fairly, which helps to reduce the impact of the monitoring scheme on the lifetime of the sensor network. Simulation results indicate that our method is able to generate accurate energy maps with much lower energy cost compared with traditional monitoring approaches. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1080/15501320902876055 | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS |
Keywords | Field | DocType |
Wireless Sensor Network, Energy Collection, Network Monitoring, In-Network Aggregation | Key distribution in wireless sensor networks,Residual energy,Computer science,Efficient energy use,Computer network,Real-time computing,Continuous monitoring,Mobile wireless sensor network,Network monitoring,Cluster analysis,Wireless sensor network,Distributed computing | Journal |
Volume | Issue | ISSN |
5 | 6 | 1550-1329 |
Citations | PageRank | References |
9 | 0.69 | 7 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edward Chan | 1 | 450 | 50.35 |
| Song Han | 2 | 40 | 3.33 |