Network Topology Management Optimization of Wireless Sensor Network (WSN)

Abstract

Network topology management is one of the critical concerns when designing a Wireless Sensor Network (WSN). In this research, four basic factors including the total production cost, sensing coverage, network connectivity and fault tolerance are considered. A mathematical model is proposed to optimize four optimization metrics corresponding to the four design factors. This approach attaches a weighting coefficient to each optimization metric to adjust their importance in the optimization model. To solve the proposed model, an Ant Colony Optimization (ACO) based metaheuristics method, called MAX-MIN Ant System (MMAS) is used. In the experiment, Greedy algorithm (Greedy) and Genetic Algorithm (GA) are also adopted to solve the proposed model. The results indicate that MMAS shows a satisfactory performance on solving the proposed model, which there is an improvement on the number of sensor nodes comparing to the result of Greedy, and a better fitness value than the result of GA.