Soft Computing Strategies for Optimized Route Selection in Wireless Sensor Network

TLDR: The paper presents the performance analysis of the evolutionary algorithms such as Genetic Algorithm, Ant lion optimization, Particle swarm optimization and Ant colony optimization and evaluates the routes obtained using the fuzzy Petri Net model to find out the optimal route for the wireless sensor networks.

Abstract: The routing in the wireless sensor networks has significant part in enhancing the functioning of the network as the improper routing methodologies and the routing deteriorates the energy of the sensor networks, affecting the lifespan of the network, leading to link failures and the connectivity problems. The necessity to improve the network performance is the main focus of the paper, so the paper presents the performance analysis of the evolutionary algorithms such as Genetic Algorithm, Ant lion optimization, Particle swarm optimization and Ant colony optimization and evaluates the routes obtained using the fuzzy Petri Net model, to find out the optimal route for the wireless sensor networks. The simulation through the python in terms of the some resource validates the optimal path in terms of energy, network life time and the packet delivery ratio.