A Swarm Inspired Probabilistic Path Selection with Congestion Control in MANETs
Congestion is a major problem in mobile ad-hoc networks. 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. 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).
KeywordsAd hoc networks Conditional probability Congestion Distance vector Swarm intelligence Transmission queue length
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