An Efficient Cluster Head Election Algorithm for Adaptative Network
Shivani Agrawal1, D. Srinivasa Rao2
1Obair Bashir Bhat, M. Tech (ECE), Swami Vivekananda Institute of Engineering and Technology, Banur, Punjab India
2Er. Birinderjit Singh, Asset. Professor, Swami Vivekananda Institute of Engineering and Technology, Banur, Punjab India
Manuscript Received on August 02, 2015. | Revised Manuscript Received on August 04, 2015. | Manuscript published on August 20, 2015. | PP: 21-24 | Volume-3 Issue-9, August 2015. | Retrieval Number: I0658083915/2015©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A wireless sensor network is a distributed real-time network configuration. The designing of a wireless sensor network should be formulated with keeping following terms in consideration such as the systems is completely ad-hoc and works with wireless channel, have limited power and with dynamically changing sets of resources. Due to this the network performance is depends on their power consumption and efficient resource consumption. In such kind of network the mobility added advantages but the mobility sometimes causes the performance losses thus network clustering techniques are helps to improve the resource utilization. Thus the proposed work indented to investigate the clustering techniques for wireless sensor network. The proposed work is an en efficient cluster head election algorithm for adaptive network. That techniques have two major disadvantages first there are no limits of connections for cluster head thus high load on cluster heads and Second during the load frequently loss of energy. In order to resolve such issue in network a new technique of cluster head selection is suggested in this proposed work. The proposed technique invigilates the nodes energy and also implements the load balancing of cluster head for improving the performance of network.
Keywords: Wireless sensor network, clustering, cluster head election.