Tri Nguyen Dang
A contract theory-based incentive mechanism for UAV-enabled VR-based services in 5G and beyond
Dang, Tri Nguyen; Manzoor, Aunas; Tun, Yan Kyaw; Kazmi, S. M. Ahsan; Han, Zhu; Hong, Choong Seon
Authors
Aunas Manzoor
Yan Kyaw Tun
Ahsan Kazmi Ahsan.Kazmi@uwe.ac.uk
Senior Lecturer in Data Science
Zhu Han
Choong Seon Hong
Abstract
The proliferation of novel infotainment services such as Virtual Reality(VR)-based services has fundamentally changed the existing mobile networks. These bandwidth-hungry services expanded at a tremendously rapid pace, thus, generating a burden of data traffic in the mobile networks. To cope with this issue, one can use Multi-access Edge Computing (MEC) to bring the resource to the edge. By doing so, we can release the burden of the core network by taking the communication, computation, and caching resources nearby the end-users (UEs). Nevertheless, due to the vast adoption of VR-enabled devices, MEC resources might be insufficient in peak times or dense settings. To overcome these challenges, we propose a system model where the service provider (SP) might rent Unmanned Area Vehicles (UAVs) from UAV service providers (USPs) to serve as micro-based stations (UBSs) that expand the service area and improve the spectrum efficiency. In which, UAV can pre-cached certain sets of VR-based contents and serve UEs via air-to-ground (A2G) communication. Furthermore, future intelligent devices are capable of 5G and B5G communication interfaces, and thus, they can communicate with UAVs via A2G links. By doing so, we can significantly reduce a considerable amount of data traffic in mobile networks. In order to successfully enable such kinds of services, an attractive incentive mechanism is required. Therefore, we propose a contract theory-based incentive mechanism for UAV-assisted MEC in VR-based infotainment services, in which the MEC offers an amount reward to a UAV for serving as a UBS in a specific location for certain time slots. We then derive an optimal contract-based scheme with individual rationality and incentive compatibility conditions. The numerical findings show that our proposed approach outperforms the Linear Pricing (LP) technique and is close to the optimal solution in terms of social welfare. Additionally, our proposed scheme significantly enhanced the fairness of utility for UAVs in asymmetric information problems.
Journal Article Type | Article |
---|---|
Acceptance Date | Apr 11, 2023 |
Online Publication Date | Apr 28, 2023 |
Publication Date | Sep 15, 2023 |
Deposit Date | Jun 24, 2023 |
Publicly Available Date | Oct 29, 2023 |
Journal | IEEE Internet of Things Journal |
Electronic ISSN | 2327-4662 |
Publisher | Institute of Electrical and Electronics Engineers |
Peer Reviewed | Peer Reviewed |
Volume | 10 |
Issue | 18 |
Pages | 16465 - 16479 |
DOI | https://doi.org/10.1109/JIOT.2023.3268320 |
Keywords | Augmented reality, Virtual reality, contract theory, computational caching, Contracts, Servers, Internet of Things, Computer science, Resource management, Streaming media, Device-to-device communication |
Public URL | https://uwe-repository.worktribe.com/output/10723707 |
Publisher URL | https://ieeexplore.ieee.org/document/10105444 |
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A contract theory-based incentive mechanism for UAV-enabled VR-based services in 5G and beyond
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Copyright Statement
This is the authors accepted version of the article ‘Dang, T. N., Manzoor, A., Tun, Y. K., Kazmi, S. M. A., Han, Z., & Hong, C. S. (2023). A contract theory-based incentive mechanism for UAV-enabled VR-based services in 5G and beyond. IEEE Internet of Things, 10(18), 16465 - 16479'. DOI: https://doi.org/10.1109/jiot.2023.3268320
The final published version is available here: https://ieeexplore.ieee.org/document/10105444
© 2023 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.
See https://www.ieee.org/publications/rights/index.html for more information.
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