Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching
Mobile Edge Caching (MEC) can be exploited for reducing redundant data transmissions and improving content delivery performance in mobile networks. However, under the MEC architecture, dynamic user preference is challenging the delivery efficiency due to the imperfect match between users' deman...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2019-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/320442 |
| _version_ | 1827282684492120064 |
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| author | Sanshan Sun Wei Jiang Gang Feng Shuang Qin Ye Yuan |
| author_facet | Sanshan Sun Wei Jiang Gang Feng Shuang Qin Ye Yuan |
| author_sort | Sanshan Sun |
| collection | DOAJ |
| description | Mobile Edge Caching (MEC) can be exploited for reducing redundant data transmissions and improving content delivery performance in mobile networks. However, under the MEC architecture, dynamic user preference is challenging the delivery efficiency due to the imperfect match between users' demands and cached content. In this paper, we propose a learning-based cooperative content caching policy to predict the content popularity and cache the desired content proactively. We formulate the optimal cooperative content caching problem as a 0-1 integer programming for minimizing the average downloading latency. After using an artificial neural network to learn content popularity, we use a greedy algorithm for its approximate solution. Numerical results validate that the proposed policy can significantly increase content cache hit rate and reduce content delivery latency when compared with popular caching strategies. |
| first_indexed | 2024-04-24T09:22:20Z |
| format | Article |
| id | doaj.art-3e1058cda2094a8fad2363d0a7b0791b |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:22:20Z |
| publishDate | 2019-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-3e1058cda2094a8fad2363d0a7b0791b2024-04-15T15:31:13ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392019-01-0126250350910.17559/TV-20190303092125Cooperative Caching with Content Popularity Prediction for Mobile Edge CachingSanshan Sun0Wei Jiang1Gang Feng2Shuang Qin3Ye Yuan4National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, ChinaNational Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, ChinaNational Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, ChinaNational Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing, ChinaMobile Edge Caching (MEC) can be exploited for reducing redundant data transmissions and improving content delivery performance in mobile networks. However, under the MEC architecture, dynamic user preference is challenging the delivery efficiency due to the imperfect match between users' demands and cached content. In this paper, we propose a learning-based cooperative content caching policy to predict the content popularity and cache the desired content proactively. We formulate the optimal cooperative content caching problem as a 0-1 integer programming for minimizing the average downloading latency. After using an artificial neural network to learn content popularity, we use a greedy algorithm for its approximate solution. Numerical results validate that the proposed policy can significantly increase content cache hit rate and reduce content delivery latency when compared with popular caching strategies.https://hrcak.srce.hr/file/320442cachingcooperativemobile edge cachingneural network |
| spellingShingle | Sanshan Sun Wei Jiang Gang Feng Shuang Qin Ye Yuan Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching Tehnički Vjesnik caching cooperative mobile edge caching neural network |
| title | Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching |
| title_full | Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching |
| title_fullStr | Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching |
| title_full_unstemmed | Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching |
| title_short | Cooperative Caching with Content Popularity Prediction for Mobile Edge Caching |
| title_sort | cooperative caching with content popularity prediction for mobile edge caching |
| topic | caching cooperative mobile edge caching neural network |
| url | https://hrcak.srce.hr/file/320442 |
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