RPRTD: Routing protocol based on remaining time to encounter nodes with destination node in delay tolerant network using artificial neural network

Delay Tolerant Network (DTN) is a kind of network that there is no continuous network connectivity among nodes. There are no end-to-end and constant connection paths from source nodes to destination nodes due to the mobility nature of nodes. In such networks there exists an inevitable long delivery delay. DTN is designed to perform properly over intermittent connections among nodes. Because of mobile nature of nodes, routing in DTN is based on store-carry-forward patterns to forward messages. Store-carry-forward means when a node receives a message from one of its contacts, it stores the message in its buffer and carries the message until it encounters another Contact node with Better conditions to Take the message to the Destination node (CBTD). Recognizing one of visited nodes as CBTD is a challenging problem. After recognizing CBTD, forwarding messages to CBTDs is required and necessary for routing efficiency and performance, because the messages will be delivered to the destination faster through CBTDs. In this paper, routing is performed by recognizing CBTDs and forwarding messages to them using RPRTD algorithm. RPRTD algorithm is based on Remaining Time to encounter nodes with Destination node (RTD). A node with smaller RTD, encounters the destination node in less time than the others. RPRTD algorithm tries to take message somehow to the node with the smallest RTD value among all nodes. RTD is calculated with the help of predicting future coordinates of nodes based on artificial neural networks (ANN). Simulation results show that this algorithm makes the best decision and efficiently determines the most appropriate and the best route to deliver messages to the destination node, increases routing performance, improves number of delivered messages, and decreases delivery delay compared to the state of the art.