Dynamic resource discovery based on preference and movement pattern similarity for large-scale social internet of things
Journal article
Authors | Li, Zhiyuan, Chen, Rulong, Liu, Lu and Min, Geyong |
---|---|
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. |
Keywords | Mobile communication; Peer-to-peer networks; Resource discovery |
Year | 2015 |
Journal | IEEE Internet of Things Journal |
Publisher | IEEE |
ISSN | 2327-4662 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/JIOT.2015.2451138 |
Web address (URL) | http://hdl.handle.net/10545/620865 |
http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
hdl:10545/620865 | |
Publication dates | 30 Jun 2015 |
Publication process dates | |
Deposited | 16 Nov 2016, 15:46 |
Rights | Archived with thanks to IEEE Internet of Things Journal |
Contributors | University of Derby |
File | File Access Level Open |
File | File Access Level Open |
https://repository.derby.ac.uk/item/92z31/dynamic-resource-discovery-based-on-preference-and-movement-pattern-similarity-for-large-scale-social-internet-of-things
Download files
68
total views0
total downloads0
views this month0
downloads this month