| As newly proposed end-to-end networks, delay tolerant networks (DTN) arecharacterized by intermittent connectivity, frequent partitions, extremely high latency,etc. Hence, traditional routing protocols for Internet are difficult to be applied efficientlyin DTN scenarios, and routing in DTN faces many new challenges. Some existedrouting algorithms send multiple copies to the network to improve the data successdelivery rate, but make the big network overhead. Some other routing algorithmsimprove success delivery rate using more network knowledge, but getting all oracleknowledge in network is impossible, because of the frequent changes of networktopology. Considering above, we proposed location prediction using Grey MarkovPrediction model, and studied the routing decisions about these locations．Firstly, using the Markov forecasting mechanism, a novel approach named Sprayand Wait Routing Algorithm Based on Grey Markov Prediction Model (SWR-GM) forDTN is proposed, which combines Grey Markov location predicting model with thespray and wait routing algorithm. According to the historical information of paths alongwhich nodes move, it predicates the location of the destination node by utilizing GreyMarkov location predicting model and uses a hybrid approach to forward packets. It canimprove the transfer directional and improve the packet success delivery rate. Secondly,most routing algorithms do not take into account the differences movement model andactivities performance of the node, the fourth chapter introduces the AdvancedSWR-GM routing algorithm (ASWR-GM). It introduces the concept of the activitycoefficient of a node (ACoN) to quantify the strength of a node’s activity performance.In addition, the algorithm sprays and forwards packets on the basis of ACoN, so it caneffectively reduce the copies of a data packet and decrease the network overhead.Simulation results show that both the proposed algorithms are proved better networkperformance under the same network conditions. |
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