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In wireless sensor networks, this exhaustion of energy will be more due to its infrastructure less nature and mobility. This may lead a node to drain their energy and also affect the performance of routing protocol and network lifetime. Several researches have gone so far for predicting node lifetime and link lifetime. To address this problem a new algorithm has been developed which utilizes the network parameters relating to dynamic nature of nodes viz. energy drain rate, relative mobility estimation to predict the route lifetime. But this has given a problem of network congestion and delay. To mitigate this problem in this paper, we proposed a particle swarm optimization based routing (PSOR). PSOR algorithm is designed to maximize the lifetime of WSNs. The algorithm uses a good strategy considering energy levels of the nodes and the lengths of the routed paths. In this paper, we have compared the performance results of our PSOR approach to the results of the Genetic algorithm. Various differently sized networks are considered, and our approach gives better results than Genetic algorithm in terms of energy consumption. The main goal of our study was to maintain network life time at a maximum, while discovering the shortest paths from the source nodes to the base node using a particle swarm based optimization technique called PSO.Particle Swarm Optimization based Routing protocol (PSOR ) where we have taken energy efficiency as major criteria for performing routing and deriving optimized path for data forwarding and processing to base node. The PSOR generates a whole new path of routing by taking energy as fitness value to judge different path and choose best optimized path whose energy consumption is less as compared to other routing paths.
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