期刊
IEEE TRANSACTIONS ON CLOUD COMPUTING
卷 11, 期 1, 页码 397-411出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCC.2021.3096467
关键词
Servers; Edge computing; Cloud computing; Distributed databases; Load management; Data processing; Data models; Data placement; data popularity; load balancing; data replication; edge computing
Edge computing is a popular computing paradigm for real-time data processing and mobile intelligence. This paper proposes a popularity-based data placement method and load-balancing strategies in edge computing. Simulation results demonstrate the effectiveness of reducing data access latency and relieving storage pressures at overloaded servers.
In recent years, edge computing has become an increasingly popular computing paradigm to enable real-time data processing and mobile intelligence. Edge computing allows computing at the edge of the network, where data is generated and distributed at the nearby edge servers to reduce the data access latency and improve data processing efficiency. One of the key challenges in data-intensive edge computing is how to place the data at the edge clouds effectively such that the access latency to the data is minimized. In this paper, we study such a data placement problem in edge computing while different data items have diverse popularity. We propose a popularity based placement method which maps both data items and edge servers to a virtual plane and places or retrieves data based on its virtual coordinate in the plane. We then further propose additional placement strategies to handle load balancing among edge servers via either offloading or data duplication. Simulation results show that our proposed strategies efficiently reduce the average path length of data access and the load-balancing strategies indeed provide an effective relief of storage pressures at certain overloaded servers.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据