On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems
On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems
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DOI：
10.1109/tnse.2021.3095040
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发表时间：
2019-12
影响因子：
6.6
通讯作者：
Baoqian Wang;Junfei Xie;K. Lu;Yan Wan;Shengli Fu
中科院分区：
文献类型：
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作者：
Baoqian Wang;Junfei Xie;K. Lu;Yan Wan;Shengli Fu
近年来，编码分布式计算(CDC)引起了人们的极大关注，因为它可以有效地处理分布式计算系统中许多对延迟敏感的计算任务。尽管有这样一个突出的特点，但仍然存在许多设计挑战和机会。本文针对具有异构性计算资源的实际计算系统，设计了一种新的基于批处理的编码计算(BPCC)方法，该方法利用了每个计算节点在完成整个任务之前都可以获得一些编码结果这一事实。为此，我们首先描述了BPCC框架的主要思想，然后通过配置运算量，为BPCC建立了一个最小化任务完成时间的优化问题。通过正式的理论分析、广泛的仿真研究和在Amazon EC2计算集群上的全面真实实验，我们证明了所提出的BPCC方案在计算效率和对不确定干扰的鲁棒性方面具有良好的性能。
In recent years, coded distributed computing (CDC) has attracted significant attention, because it can efficiently facilitate many delay-sensitive computation tasks against unexpected latencies in distributed computing systems. Despite such a salient feature, many design challenges and opportunities remain. In this paper, we focus on practical computing systems with heterogeneous computing resources, and design a novel CDC approach, called batch-processing based coded computing (BPCC), which exploits the fact that every computing node can obtain some coded results before it completes the whole task. To this end, we first describe the main idea of the BPCC framework, and then formulate an optimization problem for BPCC to minimize the task completion time by configuring the computation load. Through formal theoretical analyses, extensive simulation studies, and comprehensive real experiments on the Amazon EC2 computing clusters, we demonstrate promising performance of the proposed BPCC scheme, in terms of high computational efficiency and robustness to uncertain disturbances.