Name
Abstract | ||
|---|---|---|
Localization, the determination of geographical location of sensors is a fundamental problem in wireless sensor networks. In this paper we consider a static wireless network in which the reference nodes are static-non moving. We propose a positioning method known as hybrid optimizing algorithm (HOA) which combines steepest decent method and Taylor series expansion method. The steepest decent method converges quickly at initial iterations and has less computational complexity. The performance of Taylor series method depends on initial estimation. We conduct simulation experiments to evaluate the performance of these methods. Results show that HOA achieves better performance on position accuracy as it takes the advantages of both the methods. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SMC.2013.189 | SMC |
Keywords | Field | DocType |
taylor series method,optimisation,reference nodes,initial estimation,initial iteration,reference nodes (known location),hoa,static wireless network,wireless sensor network,positioning method,taylor series expansion method,geographical location,computational complexity,hybrid optimizing algorithm,taylor series expansion,better performance,localization,hybrid optimizing method,wireless sensor networks,hybrid senor localization algorithm,steepest decent method,hybrid sensor localization,general nodes (unknown location) | Key distribution in wireless sensor networks,Wireless network,Computer science,Algorithm,Artificial intelligence,Wireless sensor network,Taylor series method,Machine learning,Computational complexity theory,Taylor series | Conference |
ISSN | Citations | PageRank |
1062-922X | 1 | 0.36 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lichuan Liu | 1 | 80 | 7.03 |
| Geetha Mavidi | 2 | 1 | 0.36 |