A fuzzy-ACO algorithm to enhance reliability optimization through energy harvesting in WSN

Reliability optimization in Wireless Sensor Network (WSN) is obviously an important problem. The basic function of a WSN is to provide an adequate and quality data transmission as economically as possible with a reasonable level of reliability with minimum power consumption. To make the system more reliable, solar energy has been considered as energy harvesting strategy. In this paper, an algorithm aiming for reliability optimization in WSN systems is discussed. This algorithm is based on a modified Ant Colony Optimization (ACO) algorithm. The throughput obtained from Sensor Medium Access Control (SMAC) protocol considered as objective function with respect to different environmental constraints. For the input variables, fuzzy models with trapezoidal membership functions are used. The results obtained are compared with other approaches from literature and found satisfactory.