An improved approach for route selection in MANETs using genetic algorithm for smart grids applications

Smart grid (SG) is combination of power resources and communication and information technologies into the electricity grid. Main components of smart grid are sensors, smart meters, monitoring system and data management systems which controlled the flow of information between the different stakeholders. Smart grid represents a huge network of computers, routers, switches, smart meter, house application, wireless sensor, renewable energy resources, and electrical vehicles. Smart grid applications need to communication between heterogeneous environments so they need to use routing protocols to accomplish their work. Ad hoc on demand Distance Vector (AODV) developed initially for Mobile Ad Hoc Networks (MANETs) and with some improvements it can be used for smart grid applications by selecting the best path between smart grid sensors to exchange reliable data. AODV is using single routing metric in the form of the minimum number of hops which not necessary the most reliable path due to the mobility nature of MANETs. Nowadays, researchers have more the tendency to the biological evolution algorithms such as Genetic algorithm (GA) to solve optimization problem. We proposed a multi metric approach using Genetic algorithm (GA) as an optimization algorithm to get reliable data delivery approach in smart grids by using AODV as an underlying routing protocol.