Abstract
In order to reduce channel contention, support scalability and prolong the lifetime of the sensor networks, sensor nodes are often grouped into clusters. Algorithm for Cluster Establishment (ACE) is a clustering algorithm for sensor networks that uses three rounds of feedback to induce the formation of a highly efficient cover of uniform clusters over the network. In this paper, we present an optimizing algorithm for minimizing the cluster overlap of ACE. Simulation shows the proposed algorithm can efficiently eliminate the redundant cluster heads and minimize the cluster overlap.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Heinzelman, W.R., Chandrakkasan, A.: An application-specific protocol architecture for wireless microsensor networks. IEEE Transactions on wireless communications 1(4), 660–670 (2002)
Chan, H., Perrig, A.: ACE: An Emergent Algorithm for Highly Uniform Cluster Formation. In: Karl, H., Wolisz, A., Willig, A. (eds.) EWSN 2004. LNCS, vol. 2920, pp. 154–171. Springer, Heidelberg (2004)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: Energy- efficint communication protocol for wireless micro sensor networks. In: Proceedings of the Hawaiian International Conference on Systems Science, pp. 1–10. IEEE Communication Society, Stockholm (2000)
Lindsey, S., Raghavenda, C.S.: PEGSIS: Power efficient GAthering in sensor Information Systems. In: Proceedings of IEEE Aerospace Conference, pp. 3-1125-3-1130. IEEE Communications Society, Stockholm (2002)
Manjeshwar, A., Agrawal, D.P.: TEEN: a routing protocol for enhanced efficiency in wireless sensor networks. In: 1st International Workshop on Parallel and Distributed Computing Issues in Wireless Networks and Mobile Computing, pp. 2009–2015. IEEE Computer Society, San Francisco (2001)
Younis, O., Fahmy, S.: Heed: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks. IEEE Trans on Mobile Computing 3(4), 366–379 (2004)
Handy, M.J., Hasse, M., Timmermann, D.: Lower energy adaptive clustering hierarchy with deterministic cluster-head selection. In: 4th International Workshop on Mobile and Wireless Communications Network, pp. 368–372. IEEE Communications Society, Stockholm (2002)
Shin, K., Abraham, A., Han, S.Y.: Self organizing sensor networks using intelligent clustering. In: Gavrilova, M.L., Gervasi, O., Kumar, V., Tan, C.J.K., Taniar, D., Laganá, A., Mun, Y., Choo, H. (eds.) ICCSA 2006. LNCS, vol. 3983, pp. 40–49. Springer, Heidelberg (2006)
Park, S., Shin, K., Abraham, A., Han, S.: Optimized self organized sensor networks. Sensors 7, 730–742 (2007)
Chan, H., Luk, M., Perrig, A.: Using clustering information for sensor network localization. In: Prasanna, V.K., Iyengar, S.S., Spirakis, P.G., Welsh, M. (eds.) DCOSS 2005. LNCS, vol. 3560, pp. 109–125. Springer, Heidelberg (2005)
Lin, C.R., Gerla, M.: Adaptive clustering for mobile wireless networks. IEEE J. Selected Areas Commun. 15(7), 1265–1275 (1997)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hu, Q., Li, Q., Wang, X., Xiong, N., Pan, Y. (2008). An Optimal Algorithm for Minimizing Cluster Overlap of ACE. In: Li, Y., Huynh, D.T., Das, S.K., Du, DZ. (eds) Wireless Algorithms, Systems, and Applications. WASA 2008. Lecture Notes in Computer Science, vol 5258. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88582-5_38
Download citation
DOI: https://doi.org/10.1007/978-3-540-88582-5_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88581-8
Online ISBN: 978-3-540-88582-5
eBook Packages: Computer ScienceComputer Science (R0)