Development of intelligent optimization techniques to improve lifetime of wireless sensor network

Abstract

Wireless sensor network WSN is a collection of large number of autonomous nodes equipped with sensors wireless communication abilities processor memory storage and energy resource The sensor nodes used in WSN can monitor sense and transmit the data using radio communication Area coverage and connectivity are the two important factors of a sensor to be considered while deploying WSN for any application The former deals with the capability of sensor nodes which are able to observe the physical connection with respect to the distance whereas the latter deals with the capability of sensor nodes which are able to communicate In general the performance of WSN can be increased by deploying the sensor in an effective manner that is done by covering each point in a region of interest by employing at least one sensor node Hence there arises a need to find maximum coverage area through the deployment of minimum number of sensor nodes Further factors like technological advancement and increased network size also create the necessity to increase the coverage area for improved connectivity and life time of network This research work focus on constructing a connected and energy efficient sensor network for applications that expects optimal sensor placement so that the life time of the network is improved The coverage area of a sensor node can be maximized using widely studied heuristic optimization techniques like Genetic Algorithm and Particle Swarm Optimization newline