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IJSTR >> Volume 9 - Issue 4, April 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

An Energy Aware Data Aggregation In Wireless Sensor Network Using Multi Verse Optimized Connected Dominant Set

[Full Text]



K.Santhoshkumar Dr.P.Suganthi



Wireless Sensor Network (WSN), Energy, Data Aggregation, Routing, Multi-Verse Optimizer (MVO), Connected Dominating Set (CDS),Fault Tolerance.



The Wireless Sensor Network (WSN) can be defined as a self-organizing multi-hop network composed of several sensor nodes that are scattered within a particular region by means of wireless communication. The network also faces some critical barriers such as the transmission of redundant data, consumption of energy owing to heterogeneous traffic and fault tolerance. Aggregation of data is an extremely critical technique that is used for data processing in the WSN. With aggregation of data, energy consumption can be reduced by the elimination of all types of redundant data or by means of bringing down the packets forwarded. There are several routing protocols that are based on clustering which provide efficient methods to extend the WSN lifetime. It further involves large node quantity which entails the multi-hop network wherein the nodes interact for vicinity with one another that has higher routing responsibilities. Connected Dominating Set (CDS) will serve to be a backbone for the WSN as there has been no infrastructure that is fixed or any centralized management available in the WSN. Using the CDS, routing can become easier and easily adaptable to changes in topology. The problem of the CDS is extensively studied using undirected graphs in the Unit Disk Graphs (UDG), wherein every senor node has the same range of transmission. In this work, a Multi-hop - Low Energy Adaptive Clustering Hierarchy (M-LEACH) based protocol with a multiverse optimized CDS algorithm is proposed. The results have proved that the method was attain the better levels of performance in terms of the number of clusters, energy consumption, and lifetime computation. It also has a lower end-to-end delay and packet loss rate.



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