Third generation memetic optimization technique for energy efficient routing stability and load balancing in MANET

Mobile ad hoc network (MANET) is self-configuring, infrastructure-less networks with a number of mobile nodes. A load balancing is significant in routing for efficient data transmission in MANETs. Several research works have been developed for load balanced routing. But maintaining energy efficient route stability and load balancing among mobile nodes is difficulty while routing the packets. In order to overcome such limitation, self generation and co-evolution based memetic optimization (SGC-MO) technique is designed in MANET. The SGC-MO initially performs initialization process where it identifies nearby node and calculates the distance between all mobile nodes near the sender node to send the packets. Next, the SGC-MO used Memetic fitness function to identify minimum distance and high energy mobile node. After that, route path is selected to maintain route stability. Then, nodes with higher loads in the network are selected and crossover operation is performed by swapping loads between neighboring mobile nodes to balance the load. Subsequently, the weight variance of mobile node is calculated to balance the load between the neighboring nodes. Finally, mutation operator in SGC-MO detects probability of high loads node and load balancing with minimum routing overhead and higher load balancing factor for routing the packets.