Constrained App Data Caching Over Edge Server Graphs in Edge Computing Environment

Autor: Mohamed Abdelrazek, Qiang He, Feifei Chen, Hai Jin, Xiaoyu Xia, John Grundy
Rok vydání: 2022
Předmět:
Zdroj: SERVICES
ISSN: 2372-0204
Popis: Edge computing has emerged as a promising paradigm for powering a huge number of applications requiring low latency, e.g., real-time navigation, interactive gaming, virtual or augmented reality, etc. Edge computing offers highly accessible computing and storage resources, including CPU, storage and bandwidth, by deploying edge servers at base stations. With more users accessing edge apps, a huge number of data will be transmitted via edge servers between users’ devices and remote cloud servers. A service provider can cache its app data on edge servers to ensure the low data retrieval latency of its users. Due to the physical size limits of edge servers, the optimal data caching strategy must minimize overall user latency with consideration of constrained cache spaces on edge servers. From the service provider’s perspective, we formulate this Constrained Edge Data Caching (CEDC) problem and prove the NP-hardness of this CEDC problem. After that, we propose CEDC-IP, an optimal approach solved by the Integer Programming technique, to find optimal solutions to this CEDC problem. We also propose CEDC-A, an approximation algorithm with theoretical guarantee, to find approximate solutions to large-scale CEDC problems efficiently. Finally, we conduct extensive experiments on a widely-used real-world data set, and the experimental results demonstrate that both CEDC-IP and CEDC-A significantly outperform the other four representative approaches.
Databáze: OpenAIRE