Abstract
Wireless sensor network (WSN) is a group of sensor nodes deployed and resource-constrained sensor nodes aware their surroundings and communicate the sensed data to the base station through sink node. Based on environmental conditions such as sound, humidity, temperature, wind, gas sensor can be clearly determined by WSN. In sensor node deployment model, Target COVerage (TCOV) and Network CONnectivity (NCON) are the basic issues in WSNs that have found important attention in Sensor Deployment Problem. In this viewpoint, Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO) are conveyed to find optimal locations for sensor nodes. GA and PSO are evolutionary computation methods based optimisation scheme inspired from biology. The principal objective of WSN is to organise the whole sensor nodes in their related positions, thereby developing an effective network. In WSN, Many research works aspire the involvement of smart context awareness algorithm for sensor deployment issues in WSN. GA and PSO of the TCOV and NCON process are deployed as the minimisation problem.
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