Optimal Computational Distribution of Social Network Optimization in Wireless Sensor Networks

Nowadays wireless and networking technologies represent a crucial research area which involves communication and digital electronics and integrate a large amount of distributed sensing capabilities. The recent improved integration in sensing, communication and computing technologies in mobile phone and similar devices contributed to increase the penetration of Wireless Sensor Networks (WSN) concept in everyday life. In particular, in this work the computational capability of a WSN is used to perform a distributed run of the recently presented optimization Evolutionary Algorithm called Social Network Optimization (SNO). Additionally, the aim of this paper is to present a distributed implementation of SNO (called d-SNO), suitably developed for real-world distributed application problems. The distributed computation capability of the WSN is then optimized in order to have an optimally spread computational time, taking into account the different computational speed of each sensor of the network.