Integration of route lifetime prediction algorithm and particle swarm optimization algorithm for selecting reliable route in MANET

In MANET, generally nodes operate with batteries for its normal operation. The nodes tend to drain their energy even when it remains in idle mode. This exhaustion of energy will be more in MANET due to its infrastructureless nature and mobility. This may lead a node to drain their energy completely within a short period comparing with general mobile network. Due to this lack of energy, communication between two nodes gets blocked and their topology may also vary. This may drastically affect the performance of routing protocol and also affect the network lifetime. Several routing protocol studies based on node lifetime and link lifetime has been done to address this problem. To mitigate this problem a new algorithm has been developed which utilizes the network parameters relating to dynamic nature of nodes viz. energy drain rate, relative mobility estimation to predict the node lifetime and link lifetime. In addition to this it also maximizes the network lifetime. But this has given a problem of network congestion and delay. To mitigate this problem, in this paper we have implemented an algorithm by integrating route lifetime prediction algorithm along with the particle swarm optimization (PSO) algorithm. Since PSO uses for network centric localization purpose, this approach generates in-network navigational decisions by obviating centralized control thereby reducing both the congestion and delay. Hence, this network centric approach is effective in a typical MANET scenario which involves node mobility, large deployment and energy constraints.