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On the influence of start-up costs in scheduling divisible loads on bus networks

机译:关于启动成本对公交网络调度可分割负载的影响

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Optimal distribution of divisible loads in bus networks is considered in this paper. The problem of minimizing the processing time is investigated by including all the overhead components that could penalize the performance of the system, in addition to the inherent communication and computation delays. These overheads are considered to be constant additive factors to the respective communication and computation components. Closed-form solution for the processing time is derived and the influence of overheads on the optimal processing time is analyzed. We derive a necessary and sufficient condition for the existence of the optimal processing time. We then study the effect of changing the load distribution sequence on the time performance. Through rigorous analysis, an optimal sequence to distribute the load among the processors is identified, whenever it exists. In case such an optimal sequence fails to exist, we present a greedy algorithm to obtain a suboptimal sequence based on some important properties of the overhead factors. Then, the effect of granularity of the data that is divisible is considered in the analysis for the case of homogeneous networks. An integer approximation algorithm capable of generating integer values of the load fractions in time O(m), where m is the number of processors in the network, is proposed. We then show that the upper bound on the suboptimal solution generated by our algorithm lies within a radius given by the sum of the computation and communication delays. Several numerical examples are presented to illustrate the concepts.
机译:本文考虑了公交网络中可分负荷的最优分配。除了固有的通信和计算延迟之外,还通过包括所有可能会降低系统性能的开销组件,来研究使处理时间最小化的问题。这些开销被认为是各个通信和计算组件的恒定累加因子。导出了处理时间的封闭式解决方案,并分析了开销对最佳处理时间的影响。我们得出最佳处理时间的存在的充分必要条件。然后,我们研究更改负载分配顺序对时间性能的影响。通过严格的分析,可以确定在处理器之间分配负载的最佳顺序。如果这种最优序列不存在,我们将提出一种贪婪算法,以基于开销因子的一些重要属性来获得次优序列。然后,在分析均质网络的情况下,考虑了可分割数据粒度的影响。提出了一种整数近似算法,该算法能够在时间O(m)中生成负载分数的整数值,其中m是网络中的处理器数量。然后,我们表明,由我们的算法生成的次优解的上限位于由计算和通信延迟之和给出的半径内。给出了几个数值示例来说明这些概念。

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