Cooperation Based Proactive Caching in Multi-Tier Cellular Networks
The limited caching capacity of the local cache enabled Base station (BS) decreases the cache hit ratio (CHR) and user satisfaction ratio (USR). However, Cache enabled multi-tier cellular networks have been presented as a promising candidate for fifth generation networks to achieve higher CHR and US...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-09-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/18/6145 |
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| author | Fawad Ahmad Ayaz Ahmad Irshad Hussain Peerapong Uthansakul Suleman Khan |
| author_facet | Fawad Ahmad Ayaz Ahmad Irshad Hussain Peerapong Uthansakul Suleman Khan |
| author_sort | Fawad Ahmad |
| collection | DOAJ |
| description | The limited caching capacity of the local cache enabled Base station (BS) decreases the cache hit ratio (CHR) and user satisfaction ratio (USR). However, Cache enabled multi-tier cellular networks have been presented as a promising candidate for fifth generation networks to achieve higher CHR and USR through densification of networks. In addition to this, the cooperation among the BSs of various tiers for cached data transfer, intensify its significance many folds. Therefore, in this paper, we consider maximization of CHR and USR in a multi-tier cellular network. We formulate a CHR and USR problem for multi-tier cellular networks while putting major constraints on caching space of BSs of each tier. The unsupervised learning algorithms such as K-mean clustering and collaborative filtering have been used for clustering the similar BSs in each tier and estimating the content popularity respectively. A novel scheme such as cluster average popularity based collaborative filtering (CAP-CF) algorithm is employed to cache popular data and hence maximizing the CHR in each tier. Similarly, two novel methods such as intra-tier and cross-tier cooperation (ITCTC) and modified ITCTC algorithms have been employed in order to optimize the USR. Simulations results witness, that the proposed schemes yield significant performance in terms of average cache hit ratio and user satisfaction ratio compared to other conventional approaches. |
| first_indexed | 2024-03-10T16:35:09Z |
| format | Article |
| id | doaj.art-b5747da6fa9b4b9d9d95431919f79a12 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T16:35:09Z |
| publishDate | 2020-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-b5747da6fa9b4b9d9d95431919f79a122023-11-20T12:33:06ZengMDPI AGApplied Sciences2076-34172020-09-011018614510.3390/app10186145Cooperation Based Proactive Caching in Multi-Tier Cellular NetworksFawad Ahmad0Ayaz Ahmad1Irshad Hussain2Peerapong Uthansakul3Suleman Khan4Department of Electrical and Computer Engineering, COMSATS University Islamabad, Wah Campus, Wah Cantt 47040, PakistanDepartment of Electrical and Computer Engineering, COMSATS University Islamabad, Wah Campus, Wah Cantt 47040, PakistanFaculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, PakistanSchool of Telecommunication Engineering, Suranaree University of Technology, Nakhon Ratchasima 30000, ThailandFaculty of Electrical & Computer Engineering, University of Engineering and Technology, Peshawar 25000, PakistanThe limited caching capacity of the local cache enabled Base station (BS) decreases the cache hit ratio (CHR) and user satisfaction ratio (USR). However, Cache enabled multi-tier cellular networks have been presented as a promising candidate for fifth generation networks to achieve higher CHR and USR through densification of networks. In addition to this, the cooperation among the BSs of various tiers for cached data transfer, intensify its significance many folds. Therefore, in this paper, we consider maximization of CHR and USR in a multi-tier cellular network. We formulate a CHR and USR problem for multi-tier cellular networks while putting major constraints on caching space of BSs of each tier. The unsupervised learning algorithms such as K-mean clustering and collaborative filtering have been used for clustering the similar BSs in each tier and estimating the content popularity respectively. A novel scheme such as cluster average popularity based collaborative filtering (CAP-CF) algorithm is employed to cache popular data and hence maximizing the CHR in each tier. Similarly, two novel methods such as intra-tier and cross-tier cooperation (ITCTC) and modified ITCTC algorithms have been employed in order to optimize the USR. Simulations results witness, that the proposed schemes yield significant performance in terms of average cache hit ratio and user satisfaction ratio compared to other conventional approaches.https://www.mdpi.com/2076-3417/10/18/6145cachingcooperative networkmulti-tier cellular networkcontent popularitymachine learning |
| spellingShingle | Fawad Ahmad Ayaz Ahmad Irshad Hussain Peerapong Uthansakul Suleman Khan Cooperation Based Proactive Caching in Multi-Tier Cellular Networks Applied Sciences caching cooperative network multi-tier cellular network content popularity machine learning |
| title | Cooperation Based Proactive Caching in Multi-Tier Cellular Networks |
| title_full | Cooperation Based Proactive Caching in Multi-Tier Cellular Networks |
| title_fullStr | Cooperation Based Proactive Caching in Multi-Tier Cellular Networks |
| title_full_unstemmed | Cooperation Based Proactive Caching in Multi-Tier Cellular Networks |
| title_short | Cooperation Based Proactive Caching in Multi-Tier Cellular Networks |
| title_sort | cooperation based proactive caching in multi tier cellular networks |
| topic | caching cooperative network multi-tier cellular network content popularity machine learning |
| url | https://www.mdpi.com/2076-3417/10/18/6145 |
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