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On the use of meta-heuristics to increase the efficiency of online grid workflow scheduling algorithms

机译:关于使用元启发式方法提高在线网格工作流调度算法的效率

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The competitiveness of online algorithms is measured based on the correctness of the results produced and processing time efficiency. Traditionally evolutionary algorithms are not favored in online paradigms because of the large number of iterations involved in the algorithm which translates directly into processing time overhead. In this paper we describe MARS (Management Architecture for Resource Services) online scheduling algorithm which uses Simulated Annealing and concepts from Tabu Search to drastically decrease the processing time of the algorithm. The paper outlines the concepts behind MARS, the components involved and scheduling methodology used. In addition we also identify the time consuming bottlenecks in the performance of the system and how evolutionary algorithms help us soar past them.
机译:在线算法的竞争力是根据产生的结果的正确性和处理时间效率来衡量的。传统上,进化算法在在线范式中不受欢迎,因为该算法涉及大量迭代,这些迭代直接转化为处理时间开销。在本文中,我们描述了MARS(资源服务管理体系结构)在线调度算法,该算法使用模拟退火和禁忌搜索中的概念来大大减少算法的处理时间。本文概述了MARS背后的概念,所涉及的组件以及所使用的调度方法。此外,我们还确定了系统性能中耗时的瓶颈,以及进化算法如何帮助我们克服了这些瓶颈。

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