异构计算系统中实现鲁棒性的自主任务丢弃机制
Autonomous Task Dropping Mechanism to Achieve Robustness in Heterogeneous Computing Systems
摘要：
分布式计算系统的鲁棒性被定义为在参数不确定的情况下保持系统性能的能力。不确定性是异构（甚至同构）分布式计算系统中的一个关键问题，它会影响系统的鲁棒性。值得注意的是，这些系统的性能受到任务执行时间和到达时间的不确定性的干扰。因此，我们的目标是使系统对这些不确定性具有鲁棒性。考虑到任务执行时间是一个随机变量，我们使用概率分析，开发一个自主的主动任务丢弃机制，以达到我们的鲁棒性目标。具体来说，我们提供了一个数学模型，确定最优的任务丢弃决策，使系统的鲁棒性最大化。然后，我们利用的数学模型，开发一个任务丢弃启发式，实现系统的鲁棒性在一个可行的时间复杂度。虽然所提出的模型是通用的，可以应用于任何分布式系统，我们专注于异构计算（HC）系统，有更高程度的不确定性比同构系统。实验结果表明，自主主动丢弃机制可以提高系统的鲁棒性高达20%。
英文摘要：
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%.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
