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Cooperative Caching and Delivery Algorithm Based on Content Access Patterns at Network Edge

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Abstract

Mobile network performance and user Quality of Experience (QoE) will be negatively affected by the explosion of mobile data traffic. Recent research has focused on local caching at the wireless edge, as motivated by the 80/20 rule regarding content popularity. By caching popular contents at base stations (BSs), backhaul congestion and content access latency can be dramatically reduced. To address the limited storage size of BSs, an algorithm optimizing cooperative caching has been highlighted. Contents requested by mobile users that cannot be obtained locally could be transferred by cooperative BSs. In this paper, we propose a cooperative caching algorithm based on BS content access patterns. We use tensor decompositions with distance constraint to analyze interaction between users, contents and base stations. Thus, BSs with small geographical distances and similar content access patterns constitute a cooperative caching domain. Simulation results based on a real dataset of usage detail records (UDRs) demonstrate the superior performance and promising practical gains in caching of the proposed caching method compared to user clustering and BS clustering.

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Acknowledgment

This work was supported in part by the National Natural Science Foundation of China (NSFC), Grant No. 61371126. This work was financially supported by self-determined research funds of CCNU from the colleges basic research and operation of MOE (CCNU17QN0011) and specific funding for education science research by self-determined research funds of CCNU from the colleges basic research and operation of MOE (ccnu16JYKX019).

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Correspondence to Hao Jiang .

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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yang, L., Chen, Y., Li, L., Jiang, H. (2019). Cooperative Caching and Delivery Algorithm Based on Content Access Patterns at Network Edge. In: Leung, V., Zhang, H., Hu, X., Liu, Q., Liu, Z. (eds) 5G for Future Wireless Networks. 5GWN 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-030-17513-9_8

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  • DOI: https://doi.org/10.1007/978-3-030-17513-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-17512-2

  • Online ISBN: 978-3-030-17513-9

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