Cluster number variability problem in LEACH

Authors:
Huafeng Liu;Liang Li;Shiyao Jin
Affiliations:
National Lab for Parallel and Distributed Processing, Changsha, Hunan, China;National Lab for Parallel and Distributed Processing, Changsha, Hunan, China;National Lab for Parallel and Distributed Processing, Changsha, Hunan, China
Venue:
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
Year:
2006

Citing 6
Cited 1

Energy-Efficient Communication Protocol for Wireless Microsensor Networks

HICSS '00 Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 8 - Volume 8
Stochastic Modeling of Distributed, Dynamic, Randomized Clustering Protocols for Wireless Sensor Networks

ICPPW '04 Proceedings of the 2004 International Conference on Parallel Processing Workshops
Monte Carlo Simulation of LEACH Protocol for Wireless Sensor Networks

PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
SWATCH: a stepwise adaptive clustering hierarchy in wireless sensor networks

NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
Routing techniques in wireless sensor networks: a survey

IEEE Wireless Communications
An application-specific protocol architecture for wireless microsensor networks

IEEE Transactions on Wireless Communications

Cluster size optimization in sensor networks with decentralized cluster-based protocols

Computer Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

LEACH is one of the most popular hierarchical routing algorithms for sensor networks. In LEACH, the cluster number per round takes an important effect on the network lifetime. Thus the goal of the cluster head selection algorithm is to ensure that the expected number of clusters per round equals a pre-determined optimal value k. However, a slight inaccuracy is spotted in the computation of the node self-selected probability per round. As a result, the number of clusters produced by the algorithm is distributed in a large range around the target value. We propose an improved clustering scheme (I-LEACH) to correct this inaccuracy. The experimental results show that this scheme can ensure a more stable number of clusters.