Dynamic resource discovery based on preference and movement pattern similarity for large-scale social internet of things
Abstract
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.Citation
Li, Z. et al (2015) 'Dynamic Resource Discovery Based on Preference and Movement Pattern Similarity for Large-Scale Social Internet of Things', IEEE Internet of Things Journal, 3 (4):581Publisher
IEEEJournal
IEEE Internet of Things JournalDOI
10.1109/JIOT.2015.2451138Additional Links
http://ieeexplore.ieee.org/document/7140727/Type
ArticleLanguage
enISSN
2327-4662ae974a485f413a2113503eed53cd6c53
10.1109/JIOT.2015.2451138
Scopus Count
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