To Enhance the Energy of Wireless Sensor Networks to Solve Bottle Neck Problem Using Swarm Routing Approach

Abstract

This research suggest an approach for solving the Bottle Neck problem in Wireless Sensor Networks
(WSN) Using Swarm Routing Approach between Network Nodes and Clustering to reduce node transfers. We
also used several targets based on different criteria to solve the solution for optimum. Parameters such as
temperature, minimum clustering, distance to the routing route and energy efficiency were taken into
consideration to solve multi-objective problems as described above. An energy-efficient network ensures that the
network would have limited transfer of energy between nodes, and hence reduced node temperature. It increases
the resilience of nodes in the network. In this thesis, the key emphasis is on using new techniques such as
clustering and the Multiple Objective Particle Swarm Optimization (PSO) algorithm to solve the Bottle Neck
problem in WSN. The scatter sensor is located in a wider field, and is used primarily to map, classify and monitor
the location's physical or environmental conditions. Such physical environments include primarily temperature,
sound, wind, etc. It is defined as a collection of nodes placed at random in the field of the sensor. Via wireless
channels these nodes are connected to each other enabling data transfer between nodes. The MATLAB 2013
simulation has been installed for set up the WSN and swarm optimization and PSO estimation. Three executable
button has been paneled on the GUI to perform the bottle neck problem of network. Sensor node battery activity
requires algorithms which save electricity. This is needed mostly due to many factors that are not human
interference, remote areas that are unavailable, no recharging facilities, etc. When there is inadequate energy in
the node, it cannot transmit data across the network.