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Data caching optimization in the edge computing environment

conference contribution
posted on 2019-01-01, 00:00 authored by Ying Liu, Qiang He, Dequan Zheng, Mingwei Zhang, Feifei ChenFeifei Chen, Bin Zhang
With the rapid increase in the use of mobile devices in people's daily lives, mobile data traffic is exploding in recent years. In the edge computing environment where edge servers are deployed around mobile users, caching popular 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 problem with a focus on the reduction of network delay and the improvement of mobile devices' energy efficiency. In this paper, we attack the data caching 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 problem as an integer programming problem, and maximizes the revenue of the service provider while satisfying a constraint for data access latency. Extensive experiments are conducted on a real-world dataset that contains the locations of edge servers and mobile users, and the results reveal that our approach significantly outperform the baseline approaches.

History

Pagination

1-8

Location

Milan, Italy

Start date

2019-07-08

End date

2019-07-13

ISBN-13

9781728127170

Language

eng

Publication classification

EN Other conference paper

Title of proceedings

ICWS 2019 : Proceedings of the IEEE International Conference on Web Services

Event

Web Services. IEEE International Conference (2019: Milan, Italy)

Publisher

IEEE

Place of publication

Piscataway, N.J.

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