Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud
Mobile device cloud (MDC) is a collaborative cloud computing platform over which neighboring smart devices form an alliance of shared resources to mitigate resource-scarcity of an individual user device for running compute-intensive applications. A major challenge of such a platform is maximizing us...
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9462933/ |
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| author | Sajeeb Saha Md. Ahsan Habib Tamal Adhikary Md. Abdur Razzaque Md. Mustafizur Rahman Meteb Altaf Mohammad Mehedi Hassan |
| author_facet | Sajeeb Saha Md. Ahsan Habib Tamal Adhikary Md. Abdur Razzaque Md. Mustafizur Rahman Meteb Altaf Mohammad Mehedi Hassan |
| author_sort | Sajeeb Saha |
| collection | DOAJ |
| description | Mobile device cloud (MDC) is a collaborative cloud computing platform over which neighboring smart devices form an alliance of shared resources to mitigate resource-scarcity of an individual user device for running compute-intensive applications. A major challenge of such a platform is maximizing user quality-of-experience (QoE) at minimum cost while providing attractive incentives to workers’ mobile devices. In state-of-the-art works, either a voluntary task execution or merely resource-cost driven mechanism has been applied to minimize the task execution time while overlooking payment of any additional incentive to the worker devices for their quality services. In this paper, we develop a computational framework for MDC where the afore-mentioned challenging problem is formulated as a multi-objective linear programming (MOLP) optimization function that exploits reverse-auction bidding policy. Due to the NP-hardness of MOLP, we offer two greedy worker selection algorithms for maximizing user QoE or minimizing execution cost. In both algorithms, the amount of incentive awarded to a worker is determined following the QoE offered to a user. Theoretical proofs of desirable properties of the proposed incentive mechanisms are presented. Simulation results illustrate the effectiveness of our incentive algorithms compared to the state-of-the-art approaches. |
| first_indexed | 2024-12-14T05:02:27Z |
| format | Article |
| id | doaj.art-996f78bf0f2c41919ad3ee534f2f65fe |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T05:02:27Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-996f78bf0f2c41919ad3ee534f2f65fe2022-12-21T23:16:12ZengIEEEIEEE Access2169-35362021-01-019951629517910.1109/ACCESS.2021.30918449462933Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device CloudSajeeb Saha0https://orcid.org/0000-0003-2292-3829Md. Ahsan Habib1https://orcid.org/0000-0002-5694-2043Tamal Adhikary2https://orcid.org/0000-0002-3911-7076Md. Abdur Razzaque3https://orcid.org/0000-0002-2542-1923Md. Mustafizur Rahman4Meteb Altaf5https://orcid.org/0000-0002-3256-3233Mohammad Mehedi Hassan6https://orcid.org/0000-0002-3479-3606Department of Computer Science and Engineering, Green Networking Research Group, University of Dhaka, Dhaka, BangladeshDepartment of Computer Science and Engineering, Green Networking Research Group, University of Dhaka, Dhaka, BangladeshDepartment of Computer Science and Engineering, Green Networking Research Group, University of Dhaka, Dhaka, BangladeshDepartment of Computer Science and Engineering, Green Networking Research Group, University of Dhaka, Dhaka, BangladeshDepartment of Computer Science and Engineering, Green Networking Research Group, University of Dhaka, Dhaka, BangladeshAdvanced Manufacturing and Industry 4.0 Center, King Abdulaziz City for Science and Technology, Riyadh, Saudi ArabiaResearch Chair of Smart Technologies, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi ArabiaMobile device cloud (MDC) is a collaborative cloud computing platform over which neighboring smart devices form an alliance of shared resources to mitigate resource-scarcity of an individual user device for running compute-intensive applications. A major challenge of such a platform is maximizing user quality-of-experience (QoE) at minimum cost while providing attractive incentives to workers’ mobile devices. In state-of-the-art works, either a voluntary task execution or merely resource-cost driven mechanism has been applied to minimize the task execution time while overlooking payment of any additional incentive to the worker devices for their quality services. In this paper, we develop a computational framework for MDC where the afore-mentioned challenging problem is formulated as a multi-objective linear programming (MOLP) optimization function that exploits reverse-auction bidding policy. Due to the NP-hardness of MOLP, we offer two greedy worker selection algorithms for maximizing user QoE or minimizing execution cost. In both algorithms, the amount of incentive awarded to a worker is determined following the QoE offered to a user. Theoretical proofs of desirable properties of the proposed incentive mechanisms are presented. Simulation results illustrate the effectiveness of our incentive algorithms compared to the state-of-the-art approaches.https://ieeexplore.ieee.org/document/9462933/Incentive mechanismmobile device cloudquality of experiencereverse auctionuser satisfaction |
| spellingShingle | Sajeeb Saha Md. Ahsan Habib Tamal Adhikary Md. Abdur Razzaque Md. Mustafizur Rahman Meteb Altaf Mohammad Mehedi Hassan Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud IEEE Access Incentive mechanism mobile device cloud quality of experience reverse auction user satisfaction |
| title | Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud |
| title_full | Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud |
| title_fullStr | Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud |
| title_full_unstemmed | Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud |
| title_short | Quality-of-Experience-Aware Incentive Mechanism for Workers in Mobile Device Cloud |
| title_sort | quality of experience aware incentive mechanism for workers in mobile device cloud |
| topic | Incentive mechanism mobile device cloud quality of experience reverse auction user satisfaction |
| url | https://ieeexplore.ieee.org/document/9462933/ |
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