A congestion control algorithm based on probabilistic acceptance and drop in delay tolerant network

Because of the intermittent connectivity and absence of stable end-to-end paths in delay tolerant networks, a store-carry-forwarding protocol is often used to improve the delivery ratio. However, message replication may easily incur huge resource consumption and finally result in network congestion. A probabilistic acceptance and drop (PAD) algorithm is proposed, which adaptively controls congestion for delay tolerant networks. In this algorithm, the queue length and input/output rate are combined to detect congestion. Based on the congestion state, each node determines the probability of accepting or dropping message to obtain a good trade-off between high delivery ratio and low overhead. Furthermore, based on the birth-death model, the continuous time Markov chain of message copies is constructed to analyze the delivery ratio of message. Theory analysis and simulation results show that, compared with other algorithms, the PAD algorithm increases the delivery ratio by more than 130 percent with shorter average end-to-end delay and less overhead.