The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Green and Mobility-Aware Caching in 5G Networks
Abstract
With the drastic increase of mobile devices, there are more and more mobile traffic and repeated requests for content. In 5G networks, small cell base stations (SBSs) caching and caching in wireless device-to-device network can effectively decrease the mobile traffic during peak hours. Currently, most of the related work is focused on how to cache content on SBSs and on mobile devices, and it is assumed that the user can download the entire requested content through the connected SBSs and mobile devices. However, few works have taken user mobility and the randomness of contact duration into consideration. How to improve the caching strategy by exploiting user mobility is still a challenging problem. Thus, in this paper, we first investigate the problem of how to conduct caching placement on SBS and on mobile devices leveraging user mobility, aiming to maximize the cache hit ratio. Specifically, the caching placement on SBSs and on mobile devices is formulated as an integer programming problem, and submodular optimization is adopted to solve the formulated problem. Then, we give the optimal transmission power of SBSs and mobile devices to deliver the caching content in order to reduce the energy cost. Simulation results prove that our caching strategy is more efficient than other existing caching strategies in terms of both cache hit ratio and energy efficiency.
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Cites
Content delivery network slicing: QoE and cost awareness
Retal, S., Bagaa, M., Taleb, T., & Flinck, H. (2017) · 2017 IEEE International Conference on Communications (ICC) · doi:10.1109/icc.2017.7996499 · Cited by 49
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Chen, M., Yang, J., Zhou, J., Hao, Y., Zhang, J., & Youn, C.-H. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700788 · Cited by 266
Self-citationCognitive Computing: Architecture, Technologies and Intelligent Applications
Chen, M., Herrera, F., & Hwang, K. (2018) · IEEE Access · doi:10.1109/access.2018.2791469 · Cited by 242
Self-citationData-Driven Computing and Caching in 5G Networks: Architecture and Delay Analysis
Chen, M., Qian, Y., Hao, Y., Li, Y., & Song, J. (2018) · IEEE Wireless Communications · doi:10.1109/mwc.2018.1700216 · Cited by 195
Self-citationiRobot-Factory: An intelligent robot factory based on cognitive manufacturing and edge computing
Hu, L., Miao, Y., Wu, G., Hassan, M. M., & Humar, I. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2018.08.006 · Cited by 160
Self-citationHao, Y., Miao, Y., Tian, Y., Hu, L., Hossain, M. S., Muhammad, G., & Amin, S. U. (2019) · arXiv · doi:10.48550/arxiv.1901.02126 · Cited by 130
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Metadata
- Authors
- Chen, M., Hao, Y., Hu, L., Huang, K., & Lau, V. K. N.
- Venue
- IEEE Transactions on Wireless Communications
- Published
- 2017-12
- Volume
- 16
- Issue
- 12
- Pages
- 8347-8361
- ISSN
- 1536-1276 (ISSN-L)
- OpenAlex
- W2762123977
- Cited by
- 169
- References
- 1
- FWCI
- 19.45
- Type
- journal article
- Language
- en
- Open access
- closed
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- Chen, M., Hao, Y., Hu, L., Huang, K., & Lau, V. K. N. (2017). Green and Mobility-Aware Caching in 5G Networks. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2017.2760830
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