An evolutionary algorithm to the Density Control, Coverage and Routing Multi-Period Problem in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are composed of autonomous and resource-constrained (power, sensing, radios, and processors) nodes. These networks are conceived to have a large number of nodes working on monitoring phenomena. A major challenge for theses networks is to provide solutions that maximize quality of service (QoS) requirements, such as coverage and data routing, and minimize the energy consumption. This paper presents an evolutionary algorithm (EA) to solve the Density Control, Coverage and Routing Multi-Period Problem (DCCRMP) in WSN. The results are compared to the optimal solutions obtained by an Integer Linear Program model and a GRASP heuristic from the literature. The EA obtains significant improvements in both quality of solutions and computational time.