A Swarm Inspired Multipath Data Transmission with Congestion Control in Manets Using Probabilistic Approach

The major causes of network congestion are the lack of network resources and the irrational allocation of network resources. The traditional congestion control methods such as rate control, window mechanism, queue control and others can solve the congestion problem, but for the congestion due to irrational allocation fundamental solution is to make more effectively use of the network resources by adjusting the traffic routing depending on choice may be probabilistic, when congestion occurs. In mobile ad hoc networks congestion creates delay in transmission and also loss of the packet that causes wastage of time and energy on recovery. The Wireless Networks have to play an important role to adopt and execute a large no of innovative application. New challenges have come considering the major limitations of the ad hoc network like node’s limited processing power, balance the load of network (to maintain the computation of the node). To overcome the above problem some algorithm is invoked and there may be huge amount of packet loss and this leads to decrease the lifetime of the network. Based on the concept of evolutionary cooperation in swarm Ant, we use the ants swarm intelligence to reinforce good quality routes. The objective of our proposed algorithm is to identify the congestion areas between source and its neighboring nodes to the destination and thus it will help to avoid the congestion of the network in the intermediate links and also minimize the packet loss in the network. Using a new mathematical model considering the swarm-based ant intelligence concept, we found an efficient congestion control mechanism (Ant’s probabilistic transition rule).