论文标题
自主任务删除机制以实现异质计算系统的鲁棒性
Autonomous Task Dropping Mechanism to Achieve Robustness in Heterogeneous Computing Systems
论文作者
论文摘要
分布式计算系统的鲁棒性定义为在存在不确定参数的情况下保持其性能的能力。不确定性是异构（甚至均质）分布的计算系统的关键问题，使系统稳健性。值得注意的是，这些系统的性能在任务执行时间和到达中都受到不确定性的干扰。因此，我们的目标是使系统对这些不确定性进行强大的影响。将任务执行时间视为一个随机变量，我们使用概率分析来开发自主主动的任务删除机制来实现我们的稳健性目标。具体而言，我们提供了一个数学模型，该模型可以识别任务删除决策的最佳性，从而最大程度地提高了系统的鲁棒性。然后，我们利用数学模型来开发一个任务删除启发式，该任务在可行的时间复杂性中实现了系统的鲁棒性。尽管提出的模型是通用的，并且可以应用于任何分布式系统，但我们集中于异质计算（HC）系统，这些系统比同质系统更高的不确定性接触程度。实验结果表明，自主主动的掉落机制可以提高系统的鲁棒性高达20％。
Robustness of a distributed computing system is defined as the ability to maintain its performance in the presence of uncertain parameters. Uncertainty is a key problem in heterogeneous (and even homogeneous) distributed computing systems that perturbs system robustness. Notably, the performance of these systems is perturbed by uncertainty in both task execution time and arrival. Accordingly, our goal is to make the system robust against these uncertainties. Considering task execution time as a random variable, we use probabilistic analysis to develop an autonomous proactive task dropping mechanism to attain our robustness goal. Specifically, we provide a mathematical model that identifies the optimality of a task dropping decision, so that the system robustness is maximized. Then, we leverage the mathematical model to develop a task dropping heuristic that achieves the system robustness within a feasible time complexity. Although the proposed model is generic and can be applied to any distributed system, we concentrate on heterogeneous computing (HC) systems that have a higher degree of exposure to uncertainty than homogeneous systems. Experimental results demonstrate that the autonomous proactive dropping mechanism can improve the system robustness by up to 20%.
