Non-cooperative Scheduling Considered Harmful in Collaborative Volunteer Computing Environments

Bruno Donassolo, Arnaud Legrand, Cl'udio Geyer
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引用次数: 16

Abstract

Advances in inter-networking technology and computing components have enabled Volunteer Computing (VC) systems that allows volunteers to donate their computers' idle CPU cycles to a given project. BOINC is the most popular VC infrastructure today with over 580,000 hosts that deliver over 2,300 TeraFLOP per day. BOINC projects usually have hundreds of thousands of independent tasks and are interested in overall throughput. Each project has its own server which is responsible for distributing work units to clients, recovering results and validating them. The BOINC scheduling algorithms are complex and have been used for many years now. Their efficiency and fairness have been assessed in the context of throughput oriented projects. Yet, recently, burst projects, with fewer tasks and interested in response time, have emerged. Many works have proposed new scheduling algorithms to optimize individual response time but their use may be problematic in presence of other projects. In this article we show that the commonly used BOINC scheduling algorithms are unable to enforce fairness and project isolation. Burst projects may dramatically impact the performance of all other projects (burst or non-burst). To study such interactions, we perform a detailed, multi-player and multi-objective game theoretic study. Our analysis and experiments provide a good understanding on the impact of the different scheduling parameters and show that the non-cooperative optimization may result in inefficient and unfair share of the resources.
协同志愿计算环境中被认为有害的非合作调度
互联网技术和计算组件的进步使志愿计算(VC)系统成为可能,该系统允许志愿者将其计算机的空闲CPU周期捐赠给给定的项目。BOINC是当今最受欢迎的风险投资基础设施,拥有超过580,000台主机,每天交付超过2,300 TeraFLOP。BOINC项目通常有数十万个独立任务,并且对总体吞吐量感兴趣。每个项目都有自己的服务器,负责将工作单元分发给客户端,恢复结果并验证它们。BOINC调度算法比较复杂,已经使用多年。在以吞吐量为导向的项目中,对其效率和公平性进行了评估。然而,最近出现了任务更少、对响应时间更感兴趣的突发项目。许多工作已经提出了新的调度算法来优化个人的响应时间,但它们的使用可能存在其他项目的问题。在本文中,我们证明了常用的BOINC调度算法无法实现公平性和项目隔离。突发项目可能会极大地影响所有其他项目(突发或非突发)的性能。为了研究这种相互作用,我们进行了详细的、多参与者和多目标博弈论研究。我们的分析和实验很好地理解了不同调度参数的影响,并表明非合作优化可能导致资源的低效和不公平分配。
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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