一种基于边缘计算的动态分散副本放置策略

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yingying Yin, Leilei Deng
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引用次数: 2

摘要

智能手机及其应用程序在我们的日常生活中使用越来越广泛。数据到达的短延迟对这些应用程序非常重要,特别是对一些时间敏感的应用程序。为了减少传输延迟,提高用户体验,本文提出了一种适用于边缘节点的动态分散数据副本放置和管理策略。它研究位置、访问频率、延迟改进和在边缘节点上放置副本的成本,以在存储成本和减少延迟之间寻求平衡。其中,动态分散副本放置策略算法对边缘节点有负载保证,避免过载;它根据请求频率动态地创建或删除边缘节点上的数据副本。动态分散的副本放置策略是分散的,以减轻传输成本。实验结果表明,边缘计算环境下的动态分散副本放置策略算法可以大大降低传输延迟,平衡边缘节点负载,提高系统性能。动态和分散的副本放置策略还考虑了存储成本,并在许多因素之间寻求平衡。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A dynamic decentralized strategy of replica placement on edge computing
Smart phone and its applications are used more and more extensively in our daily life. Short delay of arriving data is important to these applications, especially to some time-sensitive ones. To reduce transmission latency and improve user experience, a dynamic decentralized data replica placement and management strategy which works in edge nodes is proposed in this article. It studies the location, access frequency, latency improvement, and cost spent on placing replicas on edge nodes to seek a balance between cost spent for storage and reduced latency. Specifically, dynamic and decentralized replica placement strategy algorithm has load guarantee for edge nodes to avoid overload; it dynamically create or delete data replicas on edge nodes according to the request frequency. Dynamic and decentralized replica placement strategy is decentralized to relieve transmission cost. Experiment results show that dynamic and decentralized replica placement strategy algorithm in edge computing environments can greatly reduce transmission latency, balance edge nodes load, and improve system performance. Dynamic and decentralized replica placement strategy also considers the cost spent for storage, and it pursues a balance between many factors.
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来源期刊
CiteScore
6.50
自引率
4.30%
发文量
94
审稿时长
3.6 months
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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