Trua：科学网格中灵活的用户定义可用性的高效任务复制
Trua: Efficient Task Replication for Flexible User-defined Availability in Scientific Grids
摘要：
在科学计算中失败是不可避免的。在过去的几十年里，随着科学应用和设施的规模不断扩大，找到故障的根本原因可能非常复杂，有时几乎是不可能的。不同的科学计算客户具有不同的可用性需求以及为可用性付费的不同意愿。与现有的解决方案，试图提供越来越高的可用性在科学网格，我们提出了一个模型，称为任务复制用户定义的可用性（Trua）。Trua在科学网格中提供了灵活的、用户定义的可用性，允许客户向计算提供商表达他们对可用性的需求。Trua与现有的任务复制方法有两个不同之处。首先，它依赖于从科学网格的虚拟层收集的历史故障信息。失效的可靠性模型可以用不同于任何现有分布的双峰约翰逊分布来表示。其次，它采用了一个异常检测器，以过滤出异常故障，它还采用了新的选择算法，以减轻暂时的和空间的相关性的故障，而不知道故障的根本原因的影响。我们将Trua应用于从开放科学网格（OSG）收集的真实世界的痕迹。我们的研究结果表明，Trua可以成功地满足用户定义的可用性需求。
英文摘要：
Failure is inevitable in scientific computing. As scientific applications and facilities increase their scales over the last decades, finding the root cause of a failure can be very complex or at times nearly impossible. Different scientific computing customers have varying availability demands as well as a diverse willingness to pay for availability. In contrast to existing solutions that try to provide higher and higher availability in scientific grids, we propose a model called Task Replication for User-defined Availability (Trua). Trua provides flexible, user-defined, availability in scientific grids, allowing customers to express their desire for availability to computational providers. Trua differs from existing task replication approaches in two folds. First, it relies on the historic failure information collected from the virtual layer of the scientific grids. The reliability model for the failures can be represented with a bimodal Johnson distribution which is different from any existing distributions. Second, it adopts an anomaly detector to filter out anomalous failures; it additionally adopts novel selection algorithms to mitigate the effects of temporary and spatial correlations of the failures without knowing the root cause of the failures. We apply the Trua on real-world traces collected from the Open Science Grid (OSG). Our results show that the Trua can successfully meet user-defined availability demands.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
