IMPLEMENTATIONOF IMPROVED NETWORK LIFETIME TECHNIQUEFOR WSN USING CLUSTER HEAD ROTATION AND SIMULTANEOUS RECEPTION
Journal: ICTACT Journal on Communication Technology (IJCT) (Vol.6, No. 3)Publication Date: 2015-09-01
Authors : Arun Vasanaperumal; D. Sridharan;
Page : 1141-1145
Keywords : Cluster; HEED; SIC; Energy Evaluation Factor; Cluster Head;
Abstract
There are number of potential applications of Wireless Sensor Networks (WSNs) like wild habitat monitoring, forest fire detection, military surveillance etc. All these applications are constrained for power from a stand along battery power source. So it becomes of paramount importance to conserve the energy utilized from this power source. A lot of efforts have gone into this area recently and it remains as one of the hot research areas. In order to improve network lifetime and reduce average power consumption, this study proposes a novel cluster head selection algorithm. Clustering is the preferred architecture when the numbers of nodes are larger because it results in considerable power savings for large networks as compared to other ones like tree or star. Since majority of the applications generally involve more than 30 nodes, clustering has gained widespread importance and is most used network architecture. The optimum number of clusters is first selected based on the number of nodes in the network. When the network is in operation the cluster heads in a cluster are rotated periodically based on the proposed cluster head selection algorithm to increase the network lifetime. Throughout the network single-hop communication methodology is assumed. This work will serve as an encouragement for further advances in the low power techniques for implementing Wireless Sensor Networks (WSNs).
Other Latest Articles
- ATHENS SEASONAL VARIATION OF GROUND RESISTANCE PREDICTION USING NEURAL NETWORKS
- MODERN THAMIZH SANDHI RULES GENERATOR IN NLP
- OCL-BASED TEST CASE GENERATION USING CATEGORY PARTITIONING METHOD
- MBA-LF: A NEW DATA CLUSTERING METHOD USING MODIFIED BAT ALGORITHM AND LEVY FLIGHT
- CROSSOVER OPERATORS IN GENETIC ALGORITHMS: A REVIEW
Last modified: 2016-09-15 14:39:08