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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Concurrent Scheduling: Efficient Heuristics for Online Large-Scale Data Transfers in Distributed Real-Time Environments
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Concurrent Scheduling: Efficient Heuristics for Online Large-Scale Data Transfers in Distributed Real-Time Environments

机译：并发调度：分布式实时环境中在线大规模数据传输的有效启发式

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摘要

The static staging heuristics proposed in the literature for staging the data items associated with real-time distributed applications adhere to a method by which only one data item is transferred in each communication step to optimize a specific cost function. In this paper, we first propose the extended partial path (EPP) algorithm based on the same method. In terms of maximizing the number of satisfied requests, we have analytically shown that EPP has a performance that is equal to or greater than the partial path heuristic (PPH) introduced previously, thanks to excluding the data items that cannot be satisfied by PPH from scheduling and scheduling the satisfiable data-items along their extended paths. In contrast to EPP and other data staging heuristics proposed, we develop the concurrent scheduling (CS) heuristic which allows simultaneous transfer of more than one data item in an organized fashion, thereby improving the overall performance of the staging system. At the heart of the CS heuristic are EPP and the local priority assignment method devised for solving the conflicts between data items at the intermediate nodes. The extensive simulation results further confirm the superiority of the CS heuristic over PPH
机译：文献中提出的用于暂存与实时分布式应用程序关联的数据项的静态暂存试探法遵循一种方法，通过该方法，在每个通信步骤中仅传输一个数据项以优化特定的成本函数。在本文中，我们首先基于相同的方法提出了扩展部分路径（EPP）算法。在最大化满足的请求数量方面，我们已通过分析表明，EPP的性能等于或大于先前引入的部分路径启发式（PPH），这是由于从调度中排除了PPH无法满足的数据项并沿其扩展路径安排可满足的数据项。与提出的EPP和其他数据暂存试探法相反，我们开发了并发调度（CS）试探法，该试探法允许以组织的方式同时传输多个数据项，从而提高了暂存系统的整体性能。 CS启发式技术的核心是EPP和专为解决中间节点数据项之间的冲突而设计的本地优先级分配方法。广泛的仿真结果进一步证实了CS启发式算法优于PPH的优势

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