Dynamic Resource Discovery Based on Preference and Movement Pattern Similarity for Large-Scale Social Internet of Things
IEEE Internet of Things Journal
Institute of Electrical and Electronics Engineers (IEEE)
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© 2015 IEEE.Given the wide range deployment of disconnected delay-tolerant social Internet of Things (SIoT), efficient resource discovery remains a fundamental challenge for large-scale SIoT. The existing search mechanisms over the SIoT do not consider preference similarity and are designed in Cartesian coordinates without sufficient consideration of real-world network deployment environments. In this paper, we propose a novel resource discovery mechanism in a 3-D Cartesian coordinate system with the aim of enhancing the search efficiency over the SIoT. Our scheme is based on both of preference and movement pattern similarity to achieve higher search efficiency and to reduce the system overheads of SIoT. Simulation experiments have been conducted to evaluate this new scheme in a large-scale SIoT environment. The simulation results show that our proposed scheme outperforms the state-of-the-art resource discovery schemes in terms of search efficiency and average delay.
This work was supported in part by the National Natural Science Foundation of China under Grant 61202474, in part by the Project Funded by China Postdoctoral Science Foundation under Grant 2015M570469, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20130528, and in part by the Senior Professional Scientific Research Foundation of Jiangsu University under Grant 12JDG049.
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.
Vol. 3, Iss. 4, pp. 581 - 589