Abstract
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.
The work of F. Li is partially supported by the National Natural Science Foundation of China under Grant No. 61370192 and 61432015. The work of M. Shen is partially supported by Beijing Institute of Technology Research Fund Program for Young Scholars.
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Liu, S., Li, F., Zhang, Q., Shen, M. (2015). A Markov Chain Prediction Model for Routing in Delay Tolerant Networks. In: Wang, Y., Xiong, H., Argamon, S., Li, X., Li, J. (eds) Big Data Computing and Communications. BigCom 2015. Lecture Notes in Computer Science(), vol 9196. Springer, Cham. https://doi.org/10.1007/978-3-319-22047-5_39
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DOI: https://doi.org/10.1007/978-3-319-22047-5_39
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