Publication Type
Journal Article
Version
acceptedVersion
Publication Date
7-2023
Abstract
Mobile crowdsensing (MCS) has been applied in various fields to realize data sharing, where multiple platforms and multiple Mobile Users () have appeared recently. However, aiming at mutual selection, the existing works ignore making ' utilities with the limited resources and platforms' utilities while achieving the desired sensing data quality maximum as far as possible. Thus, they cannot motivate both and platforms to participate. To address this problem, standing on both sides of and platforms with conflicting interests, we propose a Progressive two-stage Auction-based Multi-platform Multi-user Mutual Selection scheme (). Specifically, in, we treat mutual selection as a two-stage auction and devise the auction models for and platform using forward and reverse auction ideas, presenting and maximizing the utilities from their respective perspectives. Then, based on the proposed progressive two-stage auction structure, we adopt 0-1 knapsack and Myerson's price theory to construct the first stage -oriented auction and the second stage platform-oriented auction, achieving devised models. Theoretical analysis shows that is economically robust. Extensive experiments on the real dataset demonstrate that respectively promotes platforms' and ' utilities by 76.23% and 10.74 times, compared with the existing works.
Keywords
Mobile crowdsensing, mutual selection, multi-platform multi-user, utility, auction
Discipline
Information Security | Numerical Analysis and Scientific Computing
Research Areas
Cybersecurity
Publication
IEEE/ACM Transactions on Networking
First Page
1
Last Page
16
ISSN
1063-6692
Identifier
10.1109/TNET.2023.3297258
Publisher
Institute of Electrical and Electronics Engineers (IEEE) / Association for Computing Machinery (ACM)
Citation
LUO, Bin; LI, Xinghua; MIAO, Yinbin; ZHANG, Man; LIU, Ximeng; REN, Yanbing; LUO, Xizhao; and DENG, Robert H..
PAM(3)S: Progressive Two-Stage Auction-Based Multi-Platform Multi-User Mutual Selection Scheme in MCS. (2023). IEEE/ACM Transactions on Networking. 1-16.
Available at: https://ink.library.smu.edu.sg/sis_research/8181
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/TNET.2023.3297258