Threshold based locking routing strategy for delay tolerant network

Delay tolerance network probabilistic routing protocols forward message to a node by observing its predictability value to meet the message destination. However, it is vital to predict the ability of node to carry the transmitted message. For instance, the traffic confluence on the high probable nodes can produce congestion that results in the drop of previously stored messages. These drops diminish the delivery ratio because the dropped message lost its opportunity to be delivered. Since, there exist multiple copies of each message; therefore, the same node invariably receives the dropped messages from other parts of the network and causes the highest number of transmissions. Additionally, the replication from source node continues on the high probable peers even the previous copies were transmitted on the better predictable neighbors than the current. In this paper, we have proposed a novel routing method called as the adaptive threshold based locking method that maintains the contemporary status of the node based on its activity in the network. We have used the adaptive status measuring metrics such as transmit factor, drop factor and hop away count. Moreover, a threshold based locking method has been introduced to control the diffusion of messages. We have performed the comparison of existing and proposed routing methods with real time mobility traces. The proposed strategy has bolstered the delivery ratio and minimizes hop count, end-to-end delay and number of transmission.