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SIMULATION OF ERROR LATENCY AND ERROR RECOVERY IN CONCURRENT PROCESSING

机译:并行处理中的错误潜伏期和错误恢复模拟

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摘要

We have developed a probabilistic algorithm for improved error recovery in a system of concurrent processes. Simulations for various lengths of checkpoint intervals have shown that in most cases the probabilistic method is cost effective. However, implementation of the probabilistic algorithm requires knowledge of the distribution function of the latency times between error occurrence and error detection. In this paper, we present a method for obtaining an approximate empirical distribution function for the latency times using the iterative rollback method. The cost effectiveness of the probabilistic method, when based on the approximate distribution function, is investigated for various parameters (number of data points collected, length of error interval). We show that using the probabilistic algorithm in conjunction with the approximate distribution function still leads to significant cost reduction over the iterative method, while not requiring knowledge of the theoretical distribution function, making this implementation universally applicable.
机译:我们已经开发了一种概率算法,用于改善并发进程系统中的错误恢复。对各种长度的检查点间隔进行的仿真表明,在大多数情况下,概率方法是具有成本效益的。但是,概率算法的实现需要了解错误发生和错误检测之间的等待时间的分布函数。在本文中,我们提出了一种使用迭代回滚方法获得等待时间的近似经验分布函数的方法。当基于近似分布函数时,针对各种参数(收集的数据点数,错误间隔的长度)研究概率方法的成本效益。我们表明,将概率算法与近似分布函数结合使用仍可导致比迭代方法显着降低成本,同时无需了解理论分布函数,从而使该实现方式普遍适用。

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