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A new effective heuristic for the intelligent management of the preventive maintenance tasks of the distributed systems

机译:一种新的有效启发式方法,用于智能管理分布式系统的预防性维护任务

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We consider a class of scheduling problems of n weighted tasks on M identical, and parallel processors with an objective of minimizing the sum of the tasks weighted flow-times. A priority rule for total weighted flow-time (PRTWF), is then proposed for locally optimal scheduling of tasks with unequal release dates and processing times. Then, an algorithm based on a heuristic and the PRTWF, is worked out to minimize the total weighted flow-time of the given set of tasks on a single server. This algorithm is designed for implementation in a dynamic process of real-time decision-making. It is next extended to tasks scheduling (with unequal release dates and processing times) on parallel servers, while minimizing their total weighted flow-time. A lower bound of solutions is also proposed to evaluate the algorithm, with a complexity in O(n~3) in the off-line scheduling process. The rule is then used in an algorithm of on-line planning and scheduling of maintenance tasks in a large size distributed system with weighted Equipments.
机译:我们考虑一类在M个相同且并行的处理器上具有n个加权任务的调度问题,目的是最大程度地减少任务加权流时间之和。然后,提出了总加权流时间(PRTWF)的优先级规则,用于发布日期和处理时间不相等的任务的本地最佳调度。然后,基于启发式算法和PRTWF的算法被设计出来,以最小化单个服务器上给定任务集的总加权流时间。该算法是为在动态的实时决策过程中实施而设计的。接下来,它扩展到并行服务器上的任务计划(发布日期和处理时间不相等),同时最大程度地减少了它们的加权流时间。还提出了一种解决方案的下限来评估该算法,该算法在离线调度过程中的复杂度为O(n〜3)。然后将该规则用于具有加权设备的大型分布式系统中维护任务的在线计划和调度算法中。

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