Computational Intelligence Routing for Lifetime Maximization in Heterogeneous Wireless Sensor Networks
In wireless sensor networks, sensor nodes are typically power-constrained with limited lifetime, and thus it is necessary to know how long the network sustains its networking operations. Heterogeneous WSNs consists of different sensor devices with different capabilities. One of major issue in WSNs is finding the coverage distance and connectivity between sensors and sink. To increase the network lifetime, this paper proposed Swarm Intelligence, routing technique called Ant Colony Optimization (ACO). Ant colony optimization algorithm provides a natural and intrinsic way of exploration of search space of coverage area. Ants communicate with their nest-mates using chemical scents known as pheromones, Based on Pheromone trail between sensor devices the shortest path is found.