Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks
Edge caching and adaptive bitrate video streaming are two promising techniques to ensure a good video viewing experience. Edge caching can bring contents closer to users to alleviate redundant content transmissions, reduce user-perceived delay and improve transmission capability. Adaptive bitrate vi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9910181/ |
| _version_ | 1817986302646157312 |
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| author | Junfeng Xie Zhaoba Wang Youxing Chen |
| author_facet | Junfeng Xie Zhaoba Wang Youxing Chen |
| author_sort | Junfeng Xie |
| collection | DOAJ |
| description | Edge caching and adaptive bitrate video streaming are two promising techniques to ensure a good video viewing experience. Edge caching can bring contents closer to users to alleviate redundant content transmissions, reduce user-perceived delay and improve transmission capability. Adaptive bitrate video streaming is able to adaptively adjust video quality based on time-varying network conditions and different users’ preference. Due to the strong coupled relationship between caching and user association, in this article, we focus on the issue of joint caching and user association optimization for adaptive bitrate video streaming in UAV-assisted cellular networks. First, we formulate the optimization problem as a non-linear integer programming (NLIP) to minimize the content delivery delay. To solve this challenging NP-hard problem, a heuristic algorithm based on quantum-inspired evolutionary algorithm (QEA) is proposed to obtain the best caching and user association solutions iteratively. Finally, simulations are conducted to demonstrate that compared with three benchmark algorithms without joint optimization of caching and user association, the proposed algorithm can greatly improve users’ video viewing experience and achieve better system performance in terms of reducing the total content delivery delay. |
| first_indexed | 2024-04-14T00:08:05Z |
| format | Article |
| id | doaj.art-dea2a806468c4988af04fbdf90689f88 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-14T00:08:05Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-dea2a806468c4988af04fbdf90689f882022-12-22T02:23:28ZengIEEEIEEE Access2169-35362022-01-011010627510628510.1109/ACCESS.2022.32119409910181Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular NetworksJunfeng Xie0https://orcid.org/0000-0003-0633-2420Zhaoba Wang1https://orcid.org/0000-0002-0143-8149Youxing Chen2School of Information and Communication Engineering, North University of China, Taiyuan, ChinaSchool of Information and Communication Engineering, North University of China, Taiyuan, ChinaSchool of Information and Communication Engineering, North University of China, Taiyuan, ChinaEdge caching and adaptive bitrate video streaming are two promising techniques to ensure a good video viewing experience. Edge caching can bring contents closer to users to alleviate redundant content transmissions, reduce user-perceived delay and improve transmission capability. Adaptive bitrate video streaming is able to adaptively adjust video quality based on time-varying network conditions and different users’ preference. Due to the strong coupled relationship between caching and user association, in this article, we focus on the issue of joint caching and user association optimization for adaptive bitrate video streaming in UAV-assisted cellular networks. First, we formulate the optimization problem as a non-linear integer programming (NLIP) to minimize the content delivery delay. To solve this challenging NP-hard problem, a heuristic algorithm based on quantum-inspired evolutionary algorithm (QEA) is proposed to obtain the best caching and user association solutions iteratively. Finally, simulations are conducted to demonstrate that compared with three benchmark algorithms without joint optimization of caching and user association, the proposed algorithm can greatly improve users’ video viewing experience and achieve better system performance in terms of reducing the total content delivery delay.https://ieeexplore.ieee.org/document/9910181/Edge cachingadaptive bitrate video streaminguser associationunmanned aerial vehiclequantum-inspired evolutionary algorithm |
| spellingShingle | Junfeng Xie Zhaoba Wang Youxing Chen Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks IEEE Access Edge caching adaptive bitrate video streaming user association unmanned aerial vehicle quantum-inspired evolutionary algorithm |
| title | Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks |
| title_full | Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks |
| title_fullStr | Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks |
| title_full_unstemmed | Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks |
| title_short | Joint Caching and User Association Optimization for Adaptive Bitrate Video Streaming in UAV-Assisted Cellular Networks |
| title_sort | joint caching and user association optimization for adaptive bitrate video streaming in uav assisted cellular networks |
| topic | Edge caching adaptive bitrate video streaming user association unmanned aerial vehicle quantum-inspired evolutionary algorithm |
| url | https://ieeexplore.ieee.org/document/9910181/ |
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