Tails in the cloud: a survey and taxonomy of straggler management within large-scale cloud data centres
Tails in the cloud: a survey and taxonomy of straggler management within large-scale cloud data centres
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DOI：
10.1007/s11227-020-03241-x
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发表时间：
2020-03
期刊：
影响因子：
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通讯作者：
S. Gill;Ouyang Xue;Peter Garraghan
中科院分区：
文献类型：
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作者：
S. Gill;Ouyang Xue;Peter Garraghan
云计算系统正在将计算密集型和数据密集型的作业拆分为更小的任务，并使用集群以并行方式执行它们，以缩短执行时间。然而，这样的系统规模越来越大，就会出现离散者，因此在作业中执行异常缓慢的运行任务会严重影响作业性能的完成。这样的掉队者是在云计算中实现快速执行数据密集型作业的直接威胁。研究人员提出了各种不同的机制、框架和管理技术，以主动和被动地检测和减轻掉队者。在本文中，我们提出了大规模云数据中心内的离散管理技术的全面审查。我们提供了离散原因的详细分类，以及根据离散特征和属性提出的管理和缓解技术。从这篇系统综述中，我们概述了几个突出的挑战和未来可能开展的离散体研究的潜在方向。
Cloud computing systems are splitting compute- and data-intensive jobs into smaller tasks to execute them in a parallel manner using clusters to improve execution time. However, such systems at increasing scale are exposed to stragglers, whereby abnormally slow running tasks executing within a job substantially affect job performance completion. Such stragglers are a direct threat towards attaining fast execution of data-intensive jobs within cloud computing. Researchers have proposed an assortment of different mechanisms, frameworks, and management techniques to detect and mitigate stragglers both proactively and reactively. In this paper, we present a comprehensive review of straggler management techniques within large-scale cloud data centres. We provide a detailed taxonomy of straggler causes, as well as proposed management and mitigation techniques based on straggler characteristics and properties. From this systematic review, we outline several outstanding challenges and potential directions of possible future work for straggler research.