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An effective iterated greedy algorithm for reliability-oriented task allocation in distributed computing systems

机译:用于分布式计算系统中面向可靠性的任务分配的有效迭代贪婪算法

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This paper investigates the problem of allocating parallel application tasks to processors in heterogeneous distributed computing systems with the goal of maximizing the system reliability. The problem of finding an optimal task allocation for more than three processors is known to be NP-hard in the strong sense. To deal with this challenging problem, we propose a simple and effective iterative greedy algorithm to find the best possible solution within a reasonable amount of computation time. The algorithm first uses a constructive heuristic to obtain an initial assignment and iteratively improves it in a greedy way. We study the performance of the proposed algorithm over a wide range of parameters including problem size, the ratio of average communication time to average computation time, and task interaction density. The viability and effectiveness of our algorithm is demonstrated by comparing it with recently proposed task allocation algorithms for maximizing system reliability available in the literature.
机译:本文研究了在异构分布式计算系统中将并行应用程序任务分配给处理器的问题,目的是最大化系统可靠性。从强烈的意义上说,为三个以上的处理器找到最佳任务分配的问题是NP难的。为了解决这个具有挑战性的问题,我们提出了一种简单有效的迭代贪婪算法,以在合理的计算时间内找到最佳的解决方案。该算法首先使用一种构造启发式方法来获取初始分配,然后以贪婪的方式迭代地对其进行改进。我们研究了该算法在各种参数上的性能,这些参数包括问题大小,平均通信时间与平均计算时间之比以及任务交互密度。通过将其与最近提出的任务分配算法进行比较,证明了我们算法的可行性和有效性,以最大程度地利用文献中的系统可靠性。

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