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Mobile Information Systems
Volume 2017 (2017), Article ID 4789814, 14 pages
Research Article

A Distributed Relation Detection Approach in the Internet of Things

1International School of Software, Wuhan University, Wuhan, China
2Science and Technology on Parallel and Distributed Processing Laboratory, National University of Defense Technology, Changsha, China
3Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong

Correspondence should be addressed to Weiping Zhu

Received 22 May 2017; Revised 6 August 2017; Accepted 16 August 2017; Published 28 September 2017

Academic Editor: Floriano Scioscia

Copyright © 2017 Weiping Zhu 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.


In the Internet of Things, it is important to detect the various relations among objects for mining useful knowledge. Existing works on relation detection are based on centralized processing, which is not suitable for the Internet of Things owing to the unavailability of a server, one-point failure, computation bottleneck, and moving of objects. In this paper, we propose a distributed approach to detect relations among objects. We first build a system model for this problem that supports generic forms of relations and both physical time and logical time. Based on this, we design the Distributed Relation Detection Approach (DRDA), which utilizes a distributed spanning tree to detect relations using in-network processing. DRDA can coordinate the distributed tree-building process of objects and automatically change the depth of the routing tree to a proper value. Optimization among multiple relation detection tasks is also considered. Extensive simulations were performed and the results show that the proposed approach outperforms existing approaches in terms of the energy consumption.