A Weighted Network Topology Model of WSN Based on Random Geometric Graph Method

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Abstract:

Focus on the weakness of modeling WSN topology by the means of random graph theory, a new weighted topology model of WSN based on random geometric theory is proposed in this paper. For the proposed new network model, the weighting scheme of network edge take into account the property of distance decreasing effect for communication signal. It also defines the differential weight which can embody the energy consumption for network communication. Based on simulations and calculations of the measures for the network topology as well as comparison with other forms of network, the results indicate that the proposed network topology model can not only describe the interrelated connected relationship between different nodes but also verify the degree of node is subject to Poisson distribution. It also has prominent clustering effects. These properties are consist with real world networks.

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Advanced Materials Research (Volumes 962-965)

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2898-2902

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June 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] M. E. J. Newman, S. H. Strogatz, D. J. Watts, Random graphs with arbitrary degree distributions and their applications. Physics Reviews E, 2001, 64(2), p.26.

Google Scholar

[2] Xue Feng, Kumar P R. The number of neighbors needed for connectivity of wireless networks. Wireless Networks, 2004, 10(2), p.169.

DOI: 10.1023/b:wine.0000013081.09837.c0

Google Scholar

[3] Chen Li Jun, Mao Ying Chi, Chen Dao xu. et. al, The topological control of restricted average degree WSN [J], Journal of Computer, 2007(09). (In Chinese).

Google Scholar

[4] Réka Albert and Albert-László Barabási. Statistical mechanics of complex networks. Reviews of Modern Physics, 2002, 74(1), p.47.

DOI: 10.1103/revmodphys.74.47

Google Scholar

[5] Sun Limin, Li Jianzhong, Chen Yu. Wireless sensor networks, Beijing: Tsinghua university press, 2005. (In Chinese).

Google Scholar

[6] Guo Lei, Xu Xiao Ming. Complex network, Shanghai:  Scientific and technological education publishing house, 2006. (In Chinese).

Google Scholar

[7] Gaurav Sharma, Ravi R. Mazumdar. A case for hybrid sensor networks, in MobiHoc, 2006, p.366.

Google Scholar

[8] Ye Xiucai, Xu Li, Lin Liwei. Topology optimization based on small-world phenomenon in wireless sensor networks, Journal of Fujian normal university (natural science edition) 2008, 9(5), p.38.

DOI: 10.1109/isise.2008.245

Google Scholar

[9] Jason L H. System Architecture for Wireless Sensor Networks.PhD dissertation of the University of California, Berkeley, spring 2003, p.31.

Google Scholar

[10] Shelby Z, Pomalaza Raez C, Karvonen H. Energy Optimization in Multihop Wireless Embedded and Sensor Networks[J]. International Journal of Wireless Information Networks, 2005, 12, (1), p.11.

DOI: 10.1007/s10776-005-5166-1

Google Scholar