Dual layer Delay Tolerant Networks (DTN)for Congestion Control

Abstract

DualLayerDelay Tolerant Networks is a new method to give better reliability and increase the efficiency of the network. Commonly Delay Tolerant Networks (DTNs) are coupled different nodes irregularly, so packet transferring in this type of networks are time consuming and nodes are scattered here and there. Communication under sea, space communication, management of calamity, tracking animals are some applications of DTN. For these types of communication we need to arrange a sensor node, which capable to maintain consistency in the presents of any environmental changes. Using Machine Learning method provide a better lifetime, through that it can provide solution for many of current issues. Machine Learning in Delay Tolerant Network assists, proper mapping of path by adjusting to the Node arrangement variations, moderatesovercrowding, and decreases unexpected issues. This paper provides an improved method of ML techniques use with DTN. In my knowledge, this work is one of the best method to solve DTN real-time problems with ML techniques. Nowadays neural network have an important role to solve many problem facing in Delay Tolerant Networks.