International Research journal of Management Science and Technology

  ISSN 2250 - 1959 (online) ISSN 2348 - 9367 (Print) New DOI : 10.32804/IRJMST

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A SURVEY ON ENERGY EFFICIENT LOAD-BALANCED CLUSTERING TECHNIQUES FOR WIRELESS SENSOR NETWORK BASED ON VARIABLE CONVERGENCE TIME

    2 Author(s):  KRISHNAKUMAR A, DR. ANURATHA V

Vol -  8, Issue- 6 ,         Page(s) : 26 - 37  (2017 ) DOI : https://doi.org/10.32804/IRJMST

Abstract

Wireless Sensor Networks (WSN) contain a number of tiny sensors to get data from the surface where it deployed. Advancements on WSN provides a small and low-cost sensor node in order to sense the data from any environment. The data processing is carried in wireless manner where the needs for research in developing new protocols. The routing protocols are in response for the maintenance of routes of the network and to safeguard the communication. Group of disjoint, non-overlapping subsets called clusters supports high scalability and better data aggregation. Hierarchical WSNs utilize limited resources of sensor nodes extends network lifetime which is created by clusters. Continuous data transfer is done in this network through cluster head and maintaining the energy level for the nodes is an essential task. Clustering is done to increase energy of the node to some certain period. Load balancing using clustering can increase the network scalability. This paper surveys on available load balanced clustering based on variable convergence time algorithms of wireless sensor networks.

  1. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer networks, 38(4), 393-422.
  2. Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer networks, 52(12), 2292-2330.
  3. Jin, Z., Jian-Ping, Y., Si-Wang, Z., Ya-Ping, L., & Guang, L. (2009). A survey on position-based routing algorithms in wireless sensor networks. Algorithms, 2(1),158-182.
  4. Kandris, D., Tsioumas, P., Tzes, A., Nikolakopoulos, G., & Vergados, D. D. (2009). Power conservation through energy efficient routing in wireless sensor networks. Sensors, 9(9), 7320-7342.
  5. Nazir, B., & Hasbullah, H. (2010, June). Energy balanced clustering in wireless sensor network. In Information Technology (ITSim), 2010 International Symposium in (Vol. 2, pp. 569-574). IEEE.
  6. Sun, K., Peng, P., Ning, P., & Wang, C. (2006, December). Secure distributed cluster formation in wireless sensor networks. In null (pp. 131-140). IEEE.
  7. Kuila, P., & Jana, P. K. (2012). Energy efficient load-balanced clustering algorithm for wireless sensor networks. Procedia Technology, 6, 771-777.
  8. Abbasi, A. A., & Younis, M. (2007). A survey on clustering algorithms for wireless sensor networks. Computer communications, 30(14), 2826-2841.
  9. Baker, D. J., & Ephremides, A. (1981). The architectural organization of a mobile radio network via a distributed algorithm. Communications, IEEE Transactions on, 29(11), 1694-1701.
  10.  Ephremides, A., Wieselthier, J. E., & Baker, D. J. (1987). A design concept for reliable mobile radio networks with frequency hopping signaling. Proceedings of the IEEE, 75(1), 56-73.
  11. Xu, K., & Gerla, M. (2002, October). A heterogeneous routing protocol based on a new stable clustering scheme. In MILCOM 2002. Proceedings (Vol. 2, pp. 838-843). IEEE.
  12. Nagpal R., D. Coore, “An algorithm for group formation in an amorphous computer,” In: Proceedings of the 10th International Conference on Parallel and Distributed Systems (PDCS’98), Las Vegas, NV, October 1998.
  13. Banerjee, S., & Khuller, S. (2001). A clustering scheme for hierarchical control in multi-hop wireless networks. In INFOCOM 2001. Twentieth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings. IEEE (Vol. 2, pp. 1028-1037). IEEE.
  14. Bandyopadhyay, S., & Coyle, E. J. (2003, April). An energy efficient hierarchical clustering algorithm for wireless sensor networks. In INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies (Vol. 3, pp. 1713-1723). IEEE.
  15. Lin, C. R., & Gerla, M. (1997). Adaptive clustering for mobile wireless networks. Selected Areas in Communications, IEEE Journal on, 15(7), 1265-1275.
  16. Lin, C. R., & Gerla, M. (1995, November). A distributed architecture for multimedia in dynamic wireless networks. In Global Telecommunications Conference, 1995. GLOBECOM'95., IEEE (Vol. 2, pp. 1468-1472). IEEE.
  17. Kaur, M., & Kaur, J. (2013). Performance Analysis of Energy Optimization Techniques In Wireless Sensor Networks. energy, 3(3), 1126-1129.
  18. BENNANI, K., ELGHANAMI, D., & MAACH, A. (2013). ENERGY-EFFICIENT CLUSTERING BASED ON HYBRID EVOLUTIONARY ALGORITHM IN WIRELESS SENSOR NETWORK. Journal of Theoretical & Applied Information Technology, 58(1).
  19. Yu, L., Wang, N., Zhang, W., & Zheng, C. (2006, September). GROUP: A Grid-Clustering Routing Protocol for Wireless Sensor Networks. In Wireless Communications, Networking and Mobile Computing, 2006. WiCOM 2006. International Conference on (pp. 1-5). IEEE.

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