EEACE: Energy Efficient ACE Algorithm for Wireless Sensor Networks

Full Text (PDF, 134KB), PP.31-37

Views: 0 Downloads: 0

Author(s)

ZHANG Meiyan 1,* ZHENG Xiaodan 1 CAI Wenyu 1

1. Zhejiang Water Conservancy and Hydropower College, Hangzhou, China, 310018

* Corresponding author.

DOI: https://doi.org/10.5815/ijwmt.2011.06.05

Received: 6 Sep. 2011 / Revised: 11 Oct. 2011 / Accepted: 14 Nov. 2011 / Published: 15 Dec. 2011

Index Terms

Wireless Sensor Networks (WSNs), Clustering Algorithm, Energy Efficiency, Algorithm for Cluster Establishment (ACE)

Abstract

The ultimate goal of researches on Wireless Sensor Networks (WSNs) is how to improve network energy efficiency as possible as can. Certainly, there are many researches concerned to energy efficient scheme in wireless sensor networks. Dividing geographically distributed sensor nodes into different clusters in order to decrease transmission range and transmission quantity is one of traditional energy efficient strategies for WSNs. In this paper, an energy efficient ACE clustering algorithm named EEACE in short is presented to improve the performance of ACE scheme. The EEACE algorithm is derived from ACE scheme but overcomes many shortcomings of ACE and other clustering algorithms such as famous LEACH and DCHS. By dividing sensor nodes into uniform clusters with minimum communication cost, EEACE algorithm improves the network’s performance at aspect of lifetime and energy efficiency significantly. The simulation results verified that EEACE algorithm prolongs the lifetime of WSNs by more than 15% comparing with ACE and DCHS algorithm.

Cite This Paper

ZHANG Meiyan,ZHENG Xiaodan,CAI Wenyu,"EEACE: Energy Efficient ACE Algorithm for Wireless Sensor Networks", IJWMT, vol.1, no.6, pp.31-37, 2011. DOI: 10.5815/ijwmt.2011.06.05

Reference

[1]Akyildiz, IF., Su, W., Sankarasubramaniam, Y., Cayirci, E., “A survey on sensor networks,” IEEE Communications Magazine, 2002, 40(8): 102-114.

[2]Shen, B.. et al, “Cluster-Based Routing Protocols for Wireless Sensor Networks,” Journal of Software, 2006, 17(7): 1588-1600 (in Chinese).

[3]Olariu, S., Xu, Q., Zomaya, A.Y., “An Energy efficient Self-Organization Protocol for Wireless Sensor Networks, Intelligent Sensors,” Sensor Networks and Information Processing Conference, 2004: 55-60.

[4]Heinzelman, W. et al, “Energy efficient Communication Protocol for Wireless Microsensor Networks,” Proc. of the HICSS 2000, 2000: 3005-3014.

[5]S. Lindsey, C. Raghavendra, and K. M. Sivalingam, “Data Gathering Algorithms in Sensor Networks using Energy Metrics”, IEEE Trans. Parallel and Distrib. Sys., vol. 13, no. 9, Sep. 2002: 924–35.

[6]O. Younis and S. Fahmy, “Distributed Clustering in Ad hoc Sensor Networks: A Hybrid, Energy-Efficient Approach,” Proc. IEEE INFOCOM 2004, Hong Kong, China, March, 2004.

[7]Handy, M., J., Haase, M., Timmermann, D, “Low Energy Adaptive Clustering Hierarchy with Deterministic Cluster-head Selection,” Mobile and Wireless Communications Network, 2002(4): 368-372.

[8]Chan, H., Perrig, A., “ACE: An emergent algorithm for highly uniform cluster formation,” Proc. of the 1st European Workshop on Wireless Sensor Networks, 2004: 154-171.

[9]Bhardwaj, M., et al. “Upper Bounds on the Lifetime of Sensor Networks,” Proceedings of ICC 2001.

[10]Heinzelman, W., et al. “Energy-Scalable Algorithms and Protocols for Wireless Microsensor Networks,” Proc. International Conference on Acoustics, Speech and Signal Processing (ICASSP'2000).

[11]Zhang, J., Sun, Y.G., Fang, Z.H., “Energy efficient Minimum Connected Dominating Set,” Chinese Journal of Sensors and Actuators, 2004(4): 603-610.