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Admit or preserve? Addressing server failures in cloud computing task management

机译:承认或保存?解决云计算任务管理中的服务器故障

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Cloud computing task management has a critical role in the efficient operation of the cloud resources, i.e., the servers. The task management handles critical and complicated decisions, overcoming the inherent dynamic nature of cloud computing systems and the additional complexity due to the large magnitude of resources in such systems (tens of thousands of servers). Due to the fact that servers may fail, task management is required to conduct both task admissions and task preservation decisions. Moreover, both these decisions require considering future system trajectories and the interplay between preservation and admission. In this paper we study the combined problem of task admission and preservation in a dynamic environment of cloud computing systems through analysis of a queueing system based on a Markov decision process (MDP). We show that the optimal operational policy is of a double switching curve type. On face value, the extraction of the optimal policy is rather complicated, yet our analysis reveals that the optimal policy can be reduced to a single rule, since the rules can effectively be decoupled. Based on this result, we propose two heuristic approaches that approximate the optimal rule for the most relevant system settings in cloud computing systems. Our results provide a simple policy scheme for the combined admission and preservation problem that can be applied in a complex cloud computing environments, and eliminate the need for sophisticated real-time control mechanisms.
机译:云计算任务管理在云资源的有效操作中具有关键作用,即服务器。任务管理处理严重和复杂的决策,克服了云计算系统的固有动态性质以及由于这种系统中的大量资源(成千上万的服务器)而导致的额外复杂性。由于服务器可能会失败,需要任务管理来进行任务录取和任务保留决策。此外,这两个决策都需要考虑未来的系统轨迹和保存和入场之间的相互作用。本文通过基于Markov决策过程(MDP)的排队系统分析,研究了云计算系统动态环境中的任务录取和保存的组合问题。我们表明最佳操作策略是双切换曲线类型。在面值上,最佳政策的提取相当复杂,但我们的分析表明,最佳政策可以减少到单一规则,因为规则可以有效地解耦。基于此结果,我们提出了两个启发式方法,近似云计算系统中最相关的系统设置的最佳规则。我们的结果为组合的录取和保存问题提供了一个简单的策略方案,可以应用于复杂的云计算环境,并消除对复杂的实时控制机制的需求。

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