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Parallelization Scheme for an Approximate Solution to Time Constraint Problems

机译:时间约束问题近似解的并行化方案

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摘要

Solving time constraint problems in wide area distributed computing environment is a challenge. We address this challenge by providing programmers a method to express their problems based on a parallelization scheme. The scheme consists of a decomposition tree defining possible decompositions of a problem into sub-problems and the decomposition dependency graph showing the relative order of execution of sub-problems. We have developed algorithms to address the following issues of the parallelization scheme: the execution of the scheme, the dependency of sub-problems, the min-max problem related to the time constraints of decomposed components. A genetic algorithm has been developed for the max-min problem. Experiment results show the good scalability of the algorithms up to thousands of nodes in each decomposition.
机译:解决广域分布式计算环境中的时间约束问题是一个挑战。我们通过为程序员提供一种基于并行化方案表达他们的问题的方法来应对这一挑战。该方案包括一个分解树,该树定义了将问题分解为子问题的可能,分解分解图显示了子问题的相对执行顺序。我们已经开发出算法来解决并行化方案的以下问题:方案的执行,子问题的依赖性,与分解组件的时间约束有关的最小-最大问题。已经针对最大-最小问题开发了一种遗传算法。实验结果表明,该算法在每次分解中最多可支持数千个节点,具有良好的可扩展性。

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