Ant Colony based Coverage Optimization in Wireless Sensor Networks

Abstract

Maximizing the covered area of wireless sensor networks while keeping the connectivity between the nodes is one of the challenging tasks in wireless sensor networks deployment. In this paper, we propose an ant colony-based method for the problem of sensor nodes deployment to maximize the coverage area. We model sensor locations as a graph and use an adapted ant colony optimization-based method to find the best places for each sensor node. To keep the connectivity of the sensor network, every sensor must be covered by the other sensors; this is a hard constraint that is applied to the cost function as a penalty. The proposed algorithm is evaluated with different numbers of sensor nodes and sensing ranges. The simulation results showed that increasing the number of iterations in the algorithm generates a better coverage ratio with the same number of nodes. Index Terms4Wireless sensor networks, node deployment, coverage maximization, ant colony optimization.

Energy-Efficient Distributed Cluster-Tree Based Routing Protocol for Applications IoT-Based WSN

“…Moreover, the authors have integrated the K-means clustering and particle swarm optimization algorithm to construct clusters. Khoshrangbaf et al [26] proposed an optimal ant colony algorithm to advance the coverage region of WSNs and maintain the connectivity between the nodes.…”