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A Fault Tolerant Volunteer Selection Mechanism Based on Collective Impact of Resources for Volunteer Computing

机译:基于资源集体影响的志愿者计算容错志愿者选择机制

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Computing (VC) is an exciting discipline that has allowed the use of millions of volunteers connected through internet to participate in any project by donating their processing cycles. VC systems have lot of potential but also few challenges such as volunteers are not managed centrally, they can submit erroneous results (intentionally or unintentionally) or can quit at any time even while executing assigned tasks. The simple solution is to select volunteer carefully keeping in view the past performance and other measures. In this paper, we have proposed a fault tolerant framework for selecting the best available volunteer. The proposed framework consists of a volunteer grouping mechanism (based on the collective impact of processing cycles, memory etc, spot checking and make span statistics) and replication (number of replicas to be generated of a particular task) policies for the individual groups. The results have shown that the proposed mechanism has successfully decreased the make span of individual tasks and increased the overall system performance.
机译:计算(VC)是一门令人兴奋的学科,它允许通过互联网连接的数百万志愿者通过捐赠其处理周期来参与任何项目。 VC系统具有很大的潜力,但挑战也很少,例如无法对志愿者进行集中管理,他们可能会提交错误的结果(有意或无意),甚至在执行分配的任务时也可以随时退出。一种简单的解决方案是仔细选择志愿者,以了解过去的表现和其他措施。在本文中,我们提出了一个容错框架,以选择最佳的可用志愿者。提议的框架包括一个针对各个组的自愿者分组机制(基于处理周期,内存等,现场检查和建立跨度统计信息的集体影响)和复制(将为特定任务生成的副本数)策略。结果表明,所提出的机制已成功减少了单个任务的执行范围,并提高了整体系统性能。

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