An Improved Cluster-head Selection approach in wireless sensor networks

As one of the most dominant factors in clustered wireless sensor networks (WSNs), the selection of cluster-head (CH) can impact the network performance. The selection shall be subject to at least two factors. (i) The number of CHs may vary in different periods of the WSN lifetime. And (ii) this number can determine on the performance, in terms of energy consumption and WSN lifetime, etc. In this paper, we draw attention to the randomly deployed WSNs based on the independent homogeneous Poisson process, and propose an Improved Cluster-head Selection (ICS) approach. Firstly, we optimize the dynamic number of CHs. Then we obtain the suitable CHs via the improved selection procedures based on three selection phases by introducing the temporary clusters. Meanwhile, CECC-based (Common Energy Consumption Cycle) synchronization is used to coordinate the intra-/inter-cluster communication. ICS saves the energy consumption and prolongs the network lifetime. Simulation demonstrates the enhanced network performance.

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

[2]  Xianghui Wang,et al.  DECP: A Distributed Election Clustering Protocol for Heterogeneous Wireless Sensor Networks , 2007, International Conference on Computational Science.

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

[4]  Robin J. Evans,et al.  An Energy-Efficient Cluster-Head Selection Protocol for Energy-Constrained Wireless Sensor Networks , 2009, ADHOCNETS.

[5]  Gaoxi Xiao,et al.  Algorithms for Energy-Efficient Clustering in Wireless Sensor Networks , 2006, 2006 10th IEEE Singapore International Conference on Communication Systems.

[6]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[7]  Y. Bar-Ness,et al.  Distributed synchronization in wireless networks , 2008, IEEE Signal Processing Magazine.

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

[9]  S. Jardosh,et al.  Intra-Cluster Topology Creation in Wireless Sensor Networks , 2007, 2007 Third International Conference on Wireless Communication and Sensor Networks.

[10]  Catherine Rosenberg,et al.  A minimum cost heterogeneous sensor network with a lifetime constraint , 2005, IEEE Transactions on Mobile Computing.

[11]  Kaveh Pahlavan.  Principles Of Wireless Networks , 2001 .

[12]  Makoto Takizawa,et al.  A Survey on Clustering Algorithms for Wireless Sensor Networks , 2010, 2010 13th International Conference on Network-Based Information Systems.

[13]  S. Fossy,et al.  On a Voronoi Aggregative Process Related to a Bivariate Poisson Process , 1996 .

[14]  Shyamala C. Sivakumar,et al.  A Clustered Wireless Sensor Network Model Based on Log–Distance Path Loss , 2008, 6th Annual Communication Networks and Services Research Conference (cnsr 2008).

[15]  Hee Yong Youn,et al.  Optimized Clustering for Maximal Lifetime of Wireless Sensor Networks , 2006, EUC Workshops.

[16]  Wendi B. Heinzelman,et al.  Application-specific protocol architectures for wireless networks , 2000 .