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Delay-tolerant networks (DTNs) are wireless partitioned networks. Because of intermittency, mobile ad hoc network (MANET) routing protocols are not efficient in DTNs. Wildlife tracking, vehicular networks, interplanetary networks, etc. are different applications of DTN. Regarding DTN applications, different parameters should be considered while designing DTN routing protocols. Message delivery ratio, message delivery delay, overhead, message drop, etc. are some important factors that are usually considered in routing algorithms. This paper proposes a method which tries to reduce overhead and message drop while increasing message delivery ratio. Choosing the appropriate number of message copies to distribute in the network is important. Few numbers of copies can lead to message drop. So, the message cannot be delivered to the destination. On the other hand, increasing the number of copies causes overhead increase in the network. The proposed algorithm uses particle swarm optimization (PSO) in intelligent choosing of number of message copies. Regarding message delivery ratio and network overhead, PSO greatly helps in finding the suitable number of copies. In order to evaluate our method, which is called PSODTN, we compared it with epidemic routing (ER) and probabilistic routing protocol using history of encounters and transitivity (PROPHET). PSODTN helps to reduce overhead, on average, 95.6% compared to ER and PROPHET. While reducing overhead, PSODTN message delivery ratio is on average 98%.
Delay tolerant networks (DTNs) are wireless intermittent networks. DTNs have different applications such as wildlife tracking, military, and space searching. Conventional mobile ad hoc network (MANET) routing protocols are not efficient in these networks because of intermittency. DTNs use store-carry-forward (SCF) for data transferring. In SCF, nodes store the messages and carry them until finding appropriate nodes for forwarding. Message replication greatly helps to improve the delivery ratio while increasing overhead. This paper examines the use of intelligent routing to choose nodes that have more probability to reach their destination. This will help to increase the message delivery ratio while reducing overhead. The proposed method, SADTN, uses simulated annealing (SA), which has shown successful results in finding global minimal, to find the next hop. Comparison of the proposed method to previously implemented methods such as epidemic routing (ER) and Probabilistic ROuting Protocol using History of Encounters and Transitivity (PROPHET), which are usually used for evaluating other methods, shows increasing message delivery ratio and decreasing overhead in SADTN. Overhead in SADTN has on average fallen to 0.01484 of ER and 0.02325 of PROPHET. This is a great advantage of SADTN.
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