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Performance tuning policies for application level fault tolerance in distributed object systems

机译:分布式对象系统中应用程序级容错的性能调整策略

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In distributed object systems, application level fault tolerance is often attained by appropriate object replication policies. These policies aim at increasing the exhibited service availability by masking potential faults that do not recur after recovery. Existing middleware support infrastructures allow customizing object replication properties. However, since fault tolerance has a significant impact in the perceived service performance, there is a need for a suitable quantitative design technique, which allows comparing different replication policies by trading off the caused overhead cost against the achieved fault-tolerance effectiveness. We are also interested in taking into account different concerns in a combined manner (e.g. fault tolerance combined with load balancing and multithreading). This paper presents experimental evidence for the most important performance tradeoffs revealed in a simulation-based study. We considered different cases of object request loss behavior for the faulty objects, as well as, a number of request-retry strategies. The experiments took place in two different application workload levels for varied fault detection settings. We provide results for the combined effects of the studied replication policies with two specific load-balancing strategies. The presented results constitute a valuable experience report for performance tuning object replication policies for application level fault tolerance.
机译:在分布式对象系统中,应用程序级别的容错性通常是通过适当的对象复制策略来实现的。这些策略旨在通过掩盖恢复后不再出现的潜在故障来提高所展示的服务可用性。现有的中间件支持基础结构允许自定义对象复制属性。但是,由于容错对感知的服务性能有重大影响,因此需要一种合适的定量设计技术,该技术允许通过权衡造成的开销成本和实现的容错有效性来比较不同的复制策略。我们也有兴趣以组合的方式考虑不同的问题(例如,将容错与负载平衡和多线程相结合)。本文提供了基于模拟研究中最重要的性能折衷的实验证据。我们考虑了故障对象的对象请求丢失行为的不同情况,以及许多请求重试策略。实验针对不同的故障检测设置在两个不同的应用程序工作负载级别上进行。我们提供了研究复制策略与两种特定负载平衡策略的组合效果的结果。呈现的结果构成了针对应用程序级容错的性能调整对象复制策略的宝贵经验报告。

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