Dynamic Overlapping Clustering for Wireless Sensor Networks Based-on Particle Swarm Optimization
In the recent years, Wireless Sensor Network (WSN) has been one of the most interesting research topics because of its flexibility and many potential applications. However, in the applications, there are still resources constraints, including: energy, computation, and bandwidth. It is believed that clustering is the best solution for the need of energy efficiency and scalability. In order to reach the high level of energy efficiencies, mostly, the clustering algorithms avoid the possibility of overlap between clusters. But in fact, there are several applications that need the occurrence of overlaps between clusters. In this paper, we propose a Particle Swarm Optimization (PSO)-based Clustering algorithm that has capability to control the overlap between clusters but still it has an ability to reach energy efficiency. PSO is chosen because it has a light computation and can quickly reach convergence. This proposed algorithm performance is analytically and experimentally compared with clustering on LEACH. The result of the test shows that this proposed algorithm has a capability to control the rate of overlapping degree linearly. The testing on the PSO for clustering also shows the better performance than on LEACH, although there are a few problems related to its complexity.
Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E., A Survey on Sensor Networks, IEEE Communications Magazine, 40 (8), pp. 104–112, 2002.
Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H., Application Specific Protocol Architecture for Wireless Microsensor Networks, IEEE Transactions on Wireless Communciations, 1(4), pp. 660-670, 2002.
Abbasi, A.A., Younis, M., A Survey on Clustering Algorithms for Wireless Sensor Networks, Journal of Computer Communications, 30(13), pp. 2826-2841, 2007.
Krishna, P., Vaidya, N.H., Chatterjee, M.& Pradhan, D.K., A Cluster-based Approach for Routing in Dynamic Networks, ACM SIGCOMM Computer Comm. Rev., 1997.
Youssef, SALAM: A Scalable Anchor-Free Localization Algorithm for Wireless Sensor Networks, PhD dissertation, Computer Science Dept., Univ. of Maryland, 2006.
Wu, T. & Biswas, S.K., A Self-Reorganizing Slot Allocation Protocol for Multi-Cluster Sensor Networks, Proc. Fourth Int’l Conf. Information Processing in Sensor Networks (IPSN ’05), pp. 309-316, Apr. 2005.
Sim, S.H., Spencer, B.F., Jr., Zhang, M. & Xie, H.,Automated Decentralized Smart Sensor Network for Modal Analysis, Proc. SPIE Smart Structures/NDE, 2009.
Youssef, Moustafa A., Youssef, Adel & Younis, Mohamed F., Overlapping Multihop Clustering for Wireless Sensor Networks, IEEE Transactions on Parallel and Distributed Systems, 20(12), December 2009.
Rhazi, A.E., Pierre, S., A Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks, IEEE Transaction on Mobile Computing, 8(4), pp. 433-444, 2009.
Chamam, Ali, Pierre, S., On the Planning of Wireless Sensor Networks: Energy Efficient Clustering under Joint Routing and Coverage Constraints, IEEE Transaction on Mobile Computing, 8 (8), pp. 1077-1086, 2009.
Kulkarni, R.V., Venayagamoorthy, G.K., Particle Swarm Optimization in Wireless Sensor Networks: A Brief Survey, IEEE Transaction on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2), pp. 262-267, 2011.
Latiff, N.M., Tsimenidis, C.C., Sharif, B.S., Energy-aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization, The 18th AnnualIEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC’07), Athens, 2007.
Latiff, N.M., Tsimenidis, C.C., Sharif, B.S., Dynamic Clustering using Binary Multi-Objective Particle Swarm Optimization for Wireless Sensor Networks,IEEE International Conference on Mobile Adhoc and Sensor Systems (MASS 2007), Pisa, 2007.
Suharjono, Amin, Wirawan, Hendrantoro, Gamantyo, Dynamic Overlapping Clustering Algorithm for Wireless Sensor Networks, 2011 International Conference on Electrical Engineering and Informatics, Bandung, Indonesia, 17-19 July 2011.
Jin, Yan, Wang, Ling, Kim, Y. & Yang, X., EEMC: A Energy-Efficient Multi-Level Clustering Algorithm for Large-Scale Wireless Sensor Networks, Computer Networks, 52(3), pp. 542-562,
Kennedy, James & Eberhart, Russell C., Particle Swarm Optimization, Proceedings of the 1995 IEEE International Conference on Neural Networks, Piscataway, New Jersey, pp. 1942–1948, 1995.
- There are currently no refbacks.
ITB Journal Publisher, LPPM – ITB,
Center for Research and Community Services (CRCS) Building Floor 7th,
Jl. Ganesha No. 10 Bandung 40132, Indonesia,