A learning automata-based clustering algorithm for sensor networks

Clustering sensor nodes is one of the effective ways which extends the life time of sensor networks. In this paper, a learning automata-based clustering algorithm (LACA) for a sensor network is proposed. The proposed algorithm is completely distributed and independent of network size and topology. The performance of the LACA via the computer simulation was evaluated and compared with other clustering algorithms. The simulation results show the high performance of the proposed clustering algorithm.

[1]  Vinayak S. Naik,et al.  A line in the sand: a wireless sensor network for target detection, classification, and tracking , 2004, Comput. Networks.

[2]  Gregory J. Pottie,et al.  Instrumenting the world with wireless sensor networks , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[3]  Rajesh Krishnan,et al.  Efficient clustering algorithms for self-organizing wireless sensor networks , 2006, Ad Hoc Networks.

[4]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[5]  A. Durresi,et al.  Adaptive Clustering Protocol for Sensor Networks , 2005, 2005 IEEE Aerospace Conference.

[6]  Mario Gerla,et al.  Adaptive Clustering for Mobile Wireless Networks , 1997, IEEE J. Sel. Areas Commun..

[7]  Stefano Basagni,et al.  Distributed clustering for ad hoc networks , 1999, Proceedings Fourth International Symposium on Parallel Architectures, Algorithms, and Networks (I-SPAN'99).

[8]  Samir Khuller,et al.  A clustering scheme for hierarchical control in multi-hop wireless networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[9]  Murat Demirbas,et al.  Peer-to-peer spatial queries in sensor networks , 2003, Proceedings Third International Conference on Peer-to-Peer Computing (P2P2003).

[10]  Dimitrios Gunopulos,et al.  Spatial queries in sensor networks , 2005, GIS '05.

[11]  Edward J. Coyle,et al.  An energy efficient hierarchical clustering algorithm for wireless sensor networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[12]  Kumpati S. Narendra,et al.  Learning automata - an introduction , 1989 .

[13]  T. Thumthawatworn,et al.  Method for cluster heads selection in wireless sensor networks , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[14]  Min Qin,et al.  An Energy-Efficient Voting-Based Clustering Algorithm for Sensor Networks , 2005, SNPD.

[15]  Sajal K. Das,et al.  WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks , 2002, Cluster Computing.

[16]  Lui Sha,et al.  Dynamic clustering for acoustic target tracking in wireless sensor networks , 2003, IEEE Transactions on Mobile Computing.

[17]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.