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International Journal of Distributed Sensor Networks
Volume 2012 (2012), Article ID 515046, 8 pages
http://dx.doi.org/10.1155/2012/515046
Research Article

Spatial and Temporal Correlations-Based Routing Algorithm in Intermittent Connectivity Human Social Network

1School of Automation, University of Electronic Science and Technology of China, Chengdu 611731, China
2School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China

Received 13 December 2011; Accepted 14 January 2012

Academic Editor: Mo Li

Copyright © 2012 Zhou Tao et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The social network formed by people is one of the key applications of Delay-Tolerant Network (DTN). Owing to its intermittent connectivity and unique human mobility patterns, how to transmit data in an effective way is a challenging problem for the social network. In this paper, we propose the idea of Trip History Model (THM) which establishes a model on a single person's mobility, and then a Spatial and Temporal Correlations-Based Routing Algorithm (STC) is proposed. In STC, the node delivery probability is calculated according to both a node's current moving prediction and its history record to give guidance for message transmission. Our simulation results show that, compared with LABEL and PROPHET algorithms, STC effectively improves the routing performance of the network.