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Data Caching Optimization in the Edge Computing Environment

Liu Ying, Qiang He, Dequan Zheng, Xiaoyu Xia, Feifei Chen, Bin Zhang

2020IEEE Transactions on Services Computing50 citationsDOI

Abstract

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 in close proximity to mobile users, caching popular data on edge servers can ensure mobile users’ low-latency access to those data and reduce the data traffic between mobile users and the centralized cloud. Existing studies consider the data caching problem with a focus on the reduction of network delay and the improvement of mobile devices’ energy efficiency. In this article, we tackle this data caching problem in the edge computing environment from a service provider’s perspective with the aim to maximize its data caching revenue. This problem is challenging because there is a trade-off between the benefit produced and the cost incurred by caching data on edge servers. In the meantime, the constraint for data access latency must also be fulfilled. In this article, we formulate the data caching problem in the edge computing environment as an integer programming (IP) problem and prove its NP-completeness. To solve this problem effectively and efficiently in large-scale scenarios, we propose an approximation approach to find near-optimal solutions. Extensive experiments are conducted on a widely-used real-world dataset to evaluate our approaches.

Topics & Concepts

Computer scienceEdge computingDistributed computingEnhanced Data Rates for GSM EvolutionComputer networkArtificial intelligenceCaching and Content DeliveryIoT and Edge/Fog ComputingCloud Computing and Resource Management
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