Energy-Aware Constrained Relay Node Deployment and Capacity Maximization for Sustainable Data Transmission Wireless Sensor Networks


J.Ashok, S. Purushothaman, G.Kalaiarasi, P.Surendar, Associate Professor,
Department of ECE, VSB Engineering College, Tamilnadu, India.


In the recent past wireless sensor networks are finding significant area of research in various ranges of applications in data transmission environment. The sustainable data transmission plays vital role in wireless sensor network for energy aware relay node (RN) deployment to transmit and receive the message. However the major challenges faced by the researches in the existing algorithms are the generation of redundant nodes which reduces the network lifetime and energy consumption.By proposing the methodology, we want to reach the goals such as cost effectiveness, coverage, connectivity, and lifetime and data latency. In this paper, the proposed methodology has the constrained placement and varies from the existing methodologies. It provides two different methods of sensor nodes to be deployed, 1) Energy rich nodes (ERNs), and 2) Energy Limited Nodes (ELN). The problem constraint is eliminated by applying minimum weighted connected domination set (MWDCS) in a vertex weighted graph. The weight function of MWCDS is used to solve the problem constraint. This paper proposes a novel algorithm based on a Modified Particle Swarm Optimization (MPSO) approach for designing an energy-aware topology control protocol. The MPSO optimization algorithm is applied to improve the performance of wireless sensor network for energy-aware constrained relay node deployment and capacity maximization. The optimized solution is obtained by cooperatively applying MPSO and integer leaner programming (ILP) and the heuristic approach is given for the approximate solution. The effectiveness and stability of the algorithm is verified through experimental analysis and parameters such as network life time, accuracy, mean square error rate, coverage area and residual energy shows prominent results which outperforms existing counterparts.