IJCNIS Vol. 7, No. 7, 8 Jun. 2015
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Edge-based Network design spaces, Network Architectures, Wireless Sensor Networks, Energy Consumption, Network Lifetime
Limited and constrained energy resources of wireless sensor network should be used wisely to prolong sensor nodes lifetime. To achieve high energy ef?ciency and to increase wireless sensor network lifetime, sensor nodes are grouped together to form clusters. Organizing wireless sensor networks into clusters enables the ef?cient utilization of limited energy resources of the deployed sensor nodes. However, the problems of unbalanced energy consumption exist in intra and inter cluster communication, and it is tightly bound to the role and the location of a sensor nodes and cluster heads in the network. Also, clustering mechanism results in an unequal load distribution in the network. This paper presents an analytical and conceptual model of Energy-ef?cient edge-based network partitioning scheme proposed for wireless sensor networks. Also, it analyzes different network design space proposed for wireless sensor networks and evaluates their performance. From the experimental results it is observed that, with proper network organization mechanism, sensor network resources are utilized effectively to elevate network lifetime.
Muni Venkateswarlu K., A. Kandasamy, Chandrasekaran K., "Analysis of Base Station Assisted Novel Network Design Space for Edge-based WSNs", International Journal of Computer Network and Information Security(IJCNIS), vol.7, no.7, pp.53-60, 2015. DOI:10.5815/ijcnis.2015.07.07
[1]D. Bhattacharyya, T.-h. Kim, and S. Pal, “A comparative study of wireless sensor networks and their routing protocols,” Sensors, vol. 10, no. 12, pp. 10 506–10 523, 2010. [Online]. Available: http://www.mdpi.com/1424-8220/10/12/10506
[2]X. Ren and H. Yu, “Multipath disjoint routing algorithm for ad hoc wireless sensor networks,” in Eighth IEEE International Symposium on Object-Oriented Real Time Distributed Computing, 2005, pp. 253–256.
[3]J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Computer Networks, vol. 52, no. 12, pp. 2292–2330, Aug. 2008. [Online]. Available: http://dx.doi.org/10.1016/j.comnet.2008.04.002
[4]K. Akkaya and M. Younis, “A survey on routing protocols for wireless sensor networks,” Journal of Ad Hoc Networks, vol. 3, no. 3, pp. 325–349, May 2005.
[5]X. Liu, “A survey on clustering routing protocols in wireless sensor networks,” Sensors, vol. 12, no. 8, pp. 11 113–11 153, 2012.
[6]S. Soro and W. B. Heinzelman, “Prolonging the lifetime of wireless sensor networks via unequal clustering,” in Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS’05) - Workshop 12, ser. IPDPS ’05, vol. 13. Washington, DC, USA: IEEE Computer Society, April 2005, pp. 236–243. [Online]. Available:
http://dx.doi.org/10.1109/IPDPS.2005.365
[7]S. Mao and Y. Hou, “BeamStar: An edge-based approach to routing in wireless sensor networks,” IEEE Transactions on Mobile Computing, vol. 6(11), pp. 1284–1296, 2007.
[8]C. Kuong Ho, H. Jyh Ming, and H. Chieh Chuan, “CHIRON: An energy efficient chain-based hierarchical routing protocol in wireless sensor networks,” in Wireless Telecommunications Symposium (WTS 2009), 2009, pp. 1–5.
[9]W. H. Li and C. Y. Yang, “A cluster-based data routing for wireless sensor networks,” in Proceedings of ICA3PP, LNCS, Springer, vol. 5574, 2009, pp. 129–136.
[10]K. Muni Venkateswarlu, A. Kandasamy, and K. Chandrasekaran, “Energy-efficient edge-based network partitioning scheme for wireless sensor networks,” in Proceedings of International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013, 2013, pp. 1017–1022.
[11]W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energyefficient communication protocol for wireless microsensor networks,” in Proceedings of the 33rd Hawaii International Conference on System Sciences, ser. HICSS ’00, vol. 8. Washington, DC, USA: IEEE Computer Society, January 2000, pp. 8020–8029. [Online]. Available: http://dl.acm.org/citation.cfm?id=820264.820485
[12]S. Lindsey and C. Raghavendra, “PEGASIS: power-efficient gathering in sensor information systems,” in Proceedings of IEEE Aerospace Conference, no. 3, March 2002, pp. 1125–1130.
[13]C. Li, M. Ye, G. Chen, and J. Wu, “An energy-efficient unequal clustering mechanism for wireless sensor networks,” in IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, 2005, 2005, pp. 8 pp.–604.
[14]S. Lee, J. Lee, H. Sin, S. Yoo, S. Lee, J. Lee, Y. Lee, and S. Kim, “An energy-efficient distributed unequal clustering protocol for wireless sensor networks,” World Academy of Science, Engineering and Technology, vol. 48, pp. 443–447, 2008.
[15]F. e. Bai, H. h. Mou, and J. Sun, “Power-efficient zoning clustering algorithm for wireless sensor networks,” in Proceedings of International Conference on Information Engineering and Computer Science(ICIECS), 2009, pp. 1–4.
[16]Tarun Dubey and O.P. Sahu, “Omni Directional Antenna Assisted Scheme to Minimize Redundancy in Wireless Sensor Networks”, International Journal of Computer Network and Information Security, 2013, 4, pp. 57-62.
[17]P. Raghu Vamsi and Krishna Kant, “An Improved Trusted Greedy Perimeter Stateless Routing for Wireless Sensor Networks”, International Journal of Computer Network and Information Security, 2014, 11, pp. 13-19.
[18]A. Boulis, Castalia, A simulator for Wireless Sensor Networks and Body Area Networks, NICTA, Eveleigh, NSW, Australia, October 2013. [Online]. Available: https://github.com/boulis/Castalia.git