Lin, D, Wang, Q, Yang, P et al. (1 more author) (2019) A Multidimensional Reputation Evaluation Model for Mobile Crowd Sensing. In: Proceedings of the 2019 15th International Wireless Communications & Mobile Computing Conference (IWCMC). 2019 15th International Wireless Communications and Mobile Computing Conference (IWCMC), 24-28 Jun 2019, Tangier, Morocco. IEEE , pp. 2070-2073. ISBN 978-1-5386-7748-3
Abstract
The participant's reputation is vital to improve the quality of service for Mobile Crowd Sensing (MCS). A multidimensional reputation evaluation model was proposed in this paper to evaluate the participant's reputation more objectively. Different from the existing strategies, the service delay and the count of the successful as well as the failed transactions were additionally utilized to evaluate the participant's reputation. An algorithm based on Analytic Hierarchical Process (AHP) was presented to establish the reputation evaluation weight matrix. Besides, a fuzzy logic based mechanism was proposed to normalize the value of the four criteria and a dual-threshold mechanism was designed to achieve admission control more properly. Finally, extensive simulations were conducted and the simulation results confirmed the effectiveness of the reputation evaluation model.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019, IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Keywords: | mobile crowd sensing network; reputation evaluation; analytic hierarchical process |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Funding Information: | Funder Grant number Royal Society IE161218 |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Feb 2020 16:49 |
Last Modified: | 20 Feb 2020 16:00 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/iwcmc.2019.8766533 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:156699 |