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dc.contributor.authorLi, Zhiyuan
dc.contributor.authorChen, Rulong
dc.contributor.authorLiu, Lu
dc.contributor.authorMin, Geyong
dc.date.accessioned2016-11-16T15:46:32Z
dc.date.available2016-11-16T15:46:32Z
dc.date.issued2015-06-30
dc.identifier.citationLi, 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):581en
dc.identifier.issn2327-4662
dc.identifier.doi10.1109/JIOT.2015.2451138
dc.identifier.urihttp://hdl.handle.net/10545/620865
dc.description.abstractGiven 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.
dc.language.isoenen
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/7140727/en
dc.rightsArchived with thanks to IEEE Internet of Things Journalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectMobile communicationen
dc.subjectPeer-to-peer networksen
dc.subjectResource discoveryen
dc.titleDynamic resource discovery based on preference and movement pattern similarity for large-scale social internet of thingsen
dc.typeArticleen
dc.contributor.departmentUniversity of Derbyen
dc.identifier.journalIEEE Internet of Things Journalen
html.description.abstractGiven 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.


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Archived with thanks to IEEE Internet of Things Journal
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