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.

中文翻译：

---

云中的尾巴：大型云数据中心内落后者管理的调查和分类

云计算系统正在将计算和数据密集型作业拆分为较小的任务，以使用集群以并行方式执行它们以缩短执行时间。然而，这种规模越来越大的系统暴露于落后者，从而在作业中执行的异常缓慢的运行任务会显着影响作业性能的完成。这种落后者是在云计算中快速执行数据密集型作业的直接威胁。研究人员提出了一系列不同的机制、框架和管理技术，以主动和被动地检测和缓解落后者。在本文中，我们全面回顾了大型云数据中心内的落后管理技术。我们提供了落后原因的详细分类，以及基于落后者的特征和属性提出的管理和缓解技术。从这篇系统综述中，我们概述了一些突出的挑战和落后研究未来可能工作的潜在方向。