In Delay Tolerant Networks (DTNs), nodes seldom keep in contact with each other because of the disorder movements of nodes. Thus many traditional routing protocols may not be applicable in this emerging network. In recent years, many routing protocols have been proposed to improve the routing performance in DTNs, however, most of them do not fully mine the inherent regular pattern of the movements of nodes. In this paper, we propose a Markov Chain Prediction (MCP) model for routing in DTNs to mine the movements of nodes property with historical contact information and use this model to improve the delivery ratio of message transferring within the network
CITATION STYLE
Liu, S., Li, F., Zhang, Q., & Shen, M. (2015). A markov chain prediction model for routing in delay tolerant networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9196, pp. 479–490). Springer Verlag. https://doi.org/10.1007/978-3-319-22047-5_39
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