A study of subdividing hexagon-clustered WSN for power saving: Analysis and simulation

Hexagons are an ideal shape for clustering sensor networks, for it can seamlessly divide clustered areas, and is the largest regular polygon (in terms of the number of sides) that has this property. In this paper, we analyze the benefit of subdividing a hexagonal cluster for the purpose of reducing the overall power consumption in the cluster. Assuming a spatial Poisson distribution of sensor nodes in the cluster, we propose a subdivision scheme, and perform a comprehensive analytical estimate of power savings brought about by the subdivision. The analytical results show that subdivision will yield considerable saving in overall power consumption of the cluster, and the saving is heavily dependent on the nodes' transmission range and their deployment density. The limit on the depth of subdivision is also analyzed. Simulation results are presented, and their implication discussed.

[1]  Anantha P. Chandrakasan,et al.  An application-specific protocol architecture for wireless microsensor networks , 2002, IEEE Trans. Wirel. Commun..

[2]  Ameer Ahmed Abbasi,et al.  A survey on clustering algorithms for wireless sensor networks , 2007, Comput. Commun..

[3]  Jie Wu,et al.  An energy-efficient unequal clustering mechanism for wireless sensor networks , 2005, IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005..

[4]  Ossama Younis,et al.  HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks , 2004, IEEE Transactions on Mobile Computing.

[5]  Madhav V. Marathe,et al.  Algorithmic Aspects of Topology Control Problems for Ad Hoc Networks , 2002, MobiHoc '02.

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

[7]  Mitali Singh,et al.  A Hierarchical Model For Distributed Collaborative Computation In Wireless Sensor Networks , 2004, Int. J. Found. Comput. Sci..

[8]  T. Gonzalez,et al.  Minimum-energy Broadcast in Simple Graphs with Limited Node Power , 2007 .

[9]  Robert J. Marks,et al.  Minimum power broadcast trees for wireless networks: optimizing using the viability lemma , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[10]  Anthony Ephremides,et al.  Energy-Efficient Broadcast and Multicast Trees in Wireless Networks , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[11]  Ferat Sahin,et al.  Cluster-head identification in ad hoc sensor networks using particle swarm optimization , 2002, 2002 IEEE International Conference on Personal Wireless Communications.

[12]  Ossama Younis,et al.  Distributed clustering in ad-hoc sensor networks: a hybrid, energy-efficient approach , 2004, IEEE INFOCOM 2004.

[13]  Cauligi S. Raghavendra,et al.  Energy efficient broadcasting for situation awareness in ad hoc networks , 2001, International Conference on Parallel Processing, 2001..

[14]  Xiangyang Li,et al.  Constructing minimum energy mobile wireless networks , 2001, MobiHoc '01.

[15]  Tzay-Farn Shih Particle Swarm Optimization Algorithm for Energy-Efficient Cluster-Based Sensor Networks , 2006, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..