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Proactive Data Caching and Replacement in the Edge Computing Environment

conference contribution
posted on 2020-01-01, 00:00 authored by Ying Liu, Ao Zhang, Xiaoyu Xia, Feifei ChenFeifei Chen, Lei Ye, Bin Zhang, Qiang He
Mobile data traffic is exploding in recent years with the exponential growth of mobile users. In the edge computing environment where edge servers are deployed around mobile users, caching data on edge servers can ensure mobile users' fast access to those data and reduce the data traffic between mobile users and the centralized cloud. Existing studies consider the data cache and replacement problem with the consideration of the reduction of network delay and the improvement of mobile devices' energy efficiency. In this paper, we attack proactive data caching and replacement problem in the edge computing environment from the service providers' perspective, who would like to maximize their venues of caching their data. This problem is complicated because data caching produces benefits at a cost and there usually is a trade-off in-between. In this paper, we formulate the data caching and replacement problem as an integer programming problem, and maximizes the revenue of the service provider while satisfying a constraint for data access latency. We also propose an online algorithm to solve problems in large-scale scenarios. Extensive experiments are conducted on a real-world dataset that contains the locations of edge servers and mobile users.



Cloud Computing. IEEE International Conference (2020 : 13th : Beijing, China)


193 - 200




Beijing, China

Place of publication

Piscataway, N.J.

Start date


End date






Publication classification

E1 Full written paper - refereed

Title of proceedings

CLOUD 2020 : Proceedings of the IEEE 13th International Conference on Cloud Computing