GSOMCR: Multi-Constraint Genetic-Optimized QoS-Aware Routing Protocol for Smart Grids

Smart grid (SG) includes the various communication networks and manages them intelligently and effectively. One of the important challenges of the SG is routing optimization. In this paper, we propose a routing protocol, namely Genetic-based Stable Optimization Multi-Constrained Routing (GSOMCR), using the seven parameters that show the Quality of Service (QoS) guaranteed in the SG. We collect the suggested parameters in one network cost function and optimize the function by Genetic Algorithm. Appropriate parameterization of GA is very important in convergence of fitness function, used in GSOMCR. We applied the novelty of Direction-Based Crossover (DBC) operator in proposed GA. DBC uses the values of fitness function to find the best direction for function to converge. Instead of using random initializing in GA, we use the GSOMCR to show the initial population in proposed GA. Comparison of the simulation results of the GSOMCR by the other protocols shows the improvement of the network performance in routing optimization of SG.