An Improved Method to Enhanced Probability Prediction in Delay Tolerant Network

Abstract

In a Delay Tolerant Network (DTN), nodes is irregularly associated. Keeping in mind the end goal to convey message starting with one node then onto the next, message is replicated and sent to another node when the association amid the nodes is set up. The node that obtains the message accumulates it and advances its duplicate to another node it experiences. The procedure is rehashed until the point when the goal node is experienced or message life time terminates. In the proposed work, the calculation of Delivery Probabilities (DP) is performed. Then energy and node’s available buffer are taken into consideration. Here the remaining energy is used to find the encounter rate. If the energy is less and DP is higher than there is a chance of node die before reaching the destination node. So energy is also very essential component to improve the overall performance. There are many parameters used to evaluate the Delivery Probability (DP) and storage of each node is also used because in DTN all the nodes should be capable of storing the message if the path is not available. When the node encounter the another node, then it checks the remaining energy and free buffer. This method is used to ignore the issue of storing extra information about each node. To achieve this process, the time of information exchange lastly is stored in the memory of each node and dropping the quantity that the DP is improved for nodes that newly encountered. In this paper, improved method is proposed for increasing the probability prediction and transitivity of the nodes. In the simulation section, ONE tool is used for the execution of the proposed technique and show the efficiency of the work as compared to the existing techniques.