Metaheuristic approach for maximizing the lifetime of Heterogeneous wireless sensor networks

This paper attempts to undertake the study of maximizing the lifetime of Heterogeneous wireless sensor networks (WSNs). 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. We can enhance the quality of monitoring in wireless sensor networks by increasing the coverage area. One of major issue in WSNs is finding maximum number of connected coverage. This paper proposed a Swarm Intelligence, Ant Colony Optimization (ACO) based approach. 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. The methodology is based on finding the maximum number of connected covers that satisfy both sensing coverage and network connectivity. By finding the coverage area and sensing range, the network lifetime maximized and reduces the energy consumption. This approach can be used in both cases of discrete point coverage and area coverage. Local search algorithm used for further enhancement. Extensive Java Agent Framework(JADE) multi agent simulator result clearly show that the proposed approach provides more approximate, effective and efficient way for maximizing the lifetime of heterogeneous WSNs.