云资源管理的新方法:混合机器学习和任务调度

IF 3.6 2区计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS

Journal of Grid Computing Pub Date : 2023-11-13 DOI:10.1007/s10723-023-09702-w

Hong Zhou

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Novel Approach to Cloud Resource Management: Hybrid Machine Learning and Task Scheduling

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来源期刊

Journal of Grid Computing COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, THEORY & METHODS

CiteScore

8.70

自引率

9.10%

发文量

审稿时长

>12 weeks

期刊介绍： Grid Computing is an emerging technology that enables large-scale resource sharing and coordinated problem solving within distributed, often loosely coordinated groups-what are sometimes termed "virtual organizations. By providing scalable, secure, high-performance mechanisms for discovering and negotiating access to remote resources, Grid technologies promise to make it possible for scientific collaborations to share resources on an unprecedented scale, and for geographically distributed groups to work together in ways that were previously impossible. Similar technologies are being adopted within industry, where they serve as important building blocks for emerging service provider infrastructures. Even though the advantages of this technology for classes of applications have been acknowledged, research in a variety of disciplines, including not only multiple domains of computer science (networking, middleware, programming, algorithms) but also application disciplines themselves, as well as such areas as sociology and economics, is needed to broaden the applicability and scope of the current body of knowledge.