Data, User and Power Allocations for Caching in Multi-Access Edge Computing
Article
Article Title | Data, User and Power Allocations for Caching in Multi-Access Edge Computing |
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ERA Journal ID | 20981 |
Article Category | Article |
Authors | Xia, Xiaoyu (Author), Chen, Feifei (Author), He, Qiang (Author), Cui, Guangming (Author), Grundy, John C. (Author), Abdelrazek, Mohamed (Author), Xu, Xiaolong (Author) and Jin, Hai (Author) |
Journal Title | IEEE Transactions on Parallel and Distributed Systems |
Journal Citation | 33 (5), pp. 1144-1155 |
Number of Pages | 12 |
Year | 2022 |
Place of Publication | United States |
ISSN | 1045-9219 |
1558-2183 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TPDS.2021.3104241 |
Web Address (URL) | https://ieeexplore.ieee.org/document/9511831 |
Abstract | In the multi-access edge computing (MEC) environment, app vendors’ data can be cached on edge servers to ensure low-latency data retrieval. Massive users can simultaneously access edge servers with high data rates through flexible allocations of transmit power. The ability to manage networking resources offers unique opportunities to app vendors but also raises unprecedented challenges. To ensure fast data retrieval for users in the MEC environment, edge data caching must take into account the allocations of data, users, and transmit power jointly. We make the first attempt to study the Data, User, and Power Allocation (DUPA 3 ) problem, aiming to serve the most users and maximize their overall data rate. First, we formulate the DUPA 3 problem and prove its NP -completeness. Then, we model the DUPA 3 problem as a potential DUPA 3 game admitting at least one Nash equilibrium and propose a two-phase game-theoretic decentralized algorithm named DUPA 3 Game to achieve the Nash equilibrium as the solution to the DUPA 3 problem. To evaluate DUPA 3 Game, we analyze its theoretical performance and conduct extensive experiments to demonstrate its effectiveness and efficiency. |
Keywords | data allocation; Edge computing; multi-access; optimization; power allocation; user allocation |
ANZSRC Field of Research 2020 | 460605. Distributed systems and algorithms |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Deakin University |
Swinburne University of Technology | |
Monash University | |
Nanjing Tech University, China | |
Huazhong University of Science and Technology, China | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q78zw/data-user-and-power-allocations-for-caching-in-multi-access-edge-computing
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