Distributed Relation Discovery in Internet of Things

Internet of things is an emerging technology that aims to connect various smart objects in our daily life. It facilitates the information exchange and control among objects. In the Internet of things, it is important to discover various relations among objects for analyzing and mining useful knowledge. Existing works on relation discovery mainly focus on centralized processing. It is not suitable for Internet of things due to unavailable of server, one-point failure, computation bottleneck, and security and business concerns. In this paper, we propose a distributed approach to discover the relations among objects in Internet of things. We first build the distritbuted system model which may include multiple relation discovery tasks. Based on that, we design an approach utilizing distributed spanning tree to extract the relations. Rather than sending all the information to the server, the objects only need to send the information to a local leader object in our algorithm. We also discuss more about how to improve the performance of the proposed approach and how to relax the system constraints. Extensive simulation have been done and the results show that the proposed approach outperforms existing approaches in terms of the data amount of transmission.