Downloads: 111 | Views: 254
Review Papers | Computer Science & Engineering | India | Volume 3 Issue 10, October 2014 | Rating: 6.7 / 10
An Energy Efficient Hybrid Clustering Algorithm for WSNS to Increase Network Lifetime - A Review
Kanchan Deep Nagi | Gagandeep Singh [8] | Maninder Kaur [8]
Abstract: The Wireless sensor networks are used in various types of environments, where the data recording becomes the prime factor. The WSNs are famous among healthcare monitoring, weather prediction (by metrological departments), army practices, etc. The WSNs suffers from a major problem of energy efficiency and clustering overhead. These two factors are considered as the major problems in the WSNs. The WSN nodes are battery running devices, hence carry limited running time. The practices which can enhance their lifetime and reduce overhead (routing overhead, clustering overhead, buffering overhead, etc) are useful to improve their performance. In this paper, we are proposing a solution to address the problem of energy efficiency. The proposed solution is based on a previous research on wireless sensor network energy efficiency using k-means clustering algorithm. The existing algorithm has many shortcomings, which includes its non-compatibility with the heterogeneous wireless sensor networks (the most adaptable WSN paradigm), cluster head selection method without calculating cluster overhead areas, etc. In the proposed model, we are going to remove such shortcomings by using cluster overhead calculation and cluster head selection based on cluster overhead. The proposed algorithm will use means clustering algorithm for the purpose of clustering. The cluster created by means algorithm would be further used with LEACH protocol, which will manage the best route for inter-nodal communication in the cluster. This will definitely enhance the lifetime of the WSN up to a significant amount. The proposed algorithm will also be capable of reducing the routing and clustering overhead from the wireless sensor nodes.
Keywords: WSN, clustering, cluster head selection, energy efficient WSNs
Edition: Volume 3 Issue 10, October 2014,
Pages: 1141 - 1143