Hybrid BPSO Genetic Algorithms Based Life Span Extension of Wireless IOT Devices

Abstract

Information collection from unconditional geographical location was done by IOT devices. Hence life span of those devices plays an very important role. Increasing the hardware requirement for this will directly increase the cost of devices, hence logical solutions are proposed by different researcher for this issue. This paper has also resolved this issue by utilizing the hybrid genetic algorithm combination term as butterfly and particle swarm optimization. This hybrid algorithm gives an effective cluster selection method which reduce packet transfer cost in term of energy. Here paper has proposed a fitness function based on position of sensor node and energy value both so resultant clusters are better. Results are compared with existing algorithms on various size of region and number of nodes. Experiment shows that proposed BF-PSO based life span expansion is better on different evaluation parameters like number of rounds, total packet transfer.