Visible to the public Data Caching Optimization in the Edge Computing Environment

TitleData Caching Optimization in the Edge Computing Environment
Publication TypeConference Paper
Year of Publication2019
AuthorsLiu, Ying, He, Qiang, Zheng, Dequan, Zhang, Mingwei, Chen, Feifei, Zhang, Bin
Conference Name2019 IEEE International Conference on Web Services (ICWS)
Date Publishedjul
Keywordscache storage, centralized cloud, cloud computing, data access, data access latency, data cache problem, data caching optimization, data caching problem, data handling, data optimization, data popularity, delays, edge computing, edge computing environment, edge servers, Energy efficiency, information retrieval, Integer Problem (IP), integer programming, integer programming problem, Metrics, mobile computing, mobile data traffic, mobile devices, mobile users, network delay reduction, Page-Hinckley-Test (PHT), pubcrawl, resilience, Resiliency, Scalability, service provider, Web Caching

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.

Citation Keyliu_data_2019