A REAL TIME-BASED OPTIMIZED NODE LOCALIZATION TECHNIQUE FOR WIRELESS SENSOR NETWORKS

Industrial Internet of Things (IIoT)IS is playing a vital role in modern industries in terms of machine condition monitoring, early failure prediction, hazard gaseous monitoring, equipment and process monitoring etc. Sensor node location awareness is the prime requirement for any Wireless Sensor Networks (WSN) deployed in the industrial field. The wireless sensors installed in different area needs to be estimated first for further clustering and data transfer to the main control station. It's an inimitable issue to recognize and maximize the coverage of the sensor nodes to ensure high quality of service (QoS). In this paper it has been attempted to find the position of the nodes by simulations and with experiment using Cat Swarm Optimization (CSO), a new swarm-based optimization algorithm inspired from the behaviour of cats. A small wireless sensor node group is developed to test the algorithm. The number of sensor nodes localized, and the localization accuracy has been the prime factor of consideration. It has been observed that utilizing CSO algorithm offers much better results than the other renowned swarm-based optimization algorithm Particle swarm optimization (PSO). The quick searching nature CSO algorithm helped to find the localization faster with best positioning accuracy and stability in wireless sensor network node localization.