A Historic-Best Particle Swarm Optimization Approach for Trust-based Routing in Smart Grid Networks

The increasing energy demand and distributed generation required the electric power grid's modernization and paved the way for Smart Grid Networks (SGN). Such networks employ power and information flow to monitor and control the power grid through digital communication technologies. Managing such information towards data acquisition and routing plays a significant role in SGN since routing on the smart grids requires several steps regarding the communication network. It has been shown that wireless sensor networks (WSNs) improve several processes in the smart grid industry. This paper proposes a trust-aware routing-based version of the Particle Swarm optimization (PSO), the Historic-Best PSO. The paper employs such a technique in trust-aware compressed sensing-based data aggregation in clustered WSNs to improve communication. The model's performance is evaluated against two other nature-inspired algorithms for routing optimization in SGN.