On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems

doi:10.1109/TNSE.2021.3095040

On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems

2021-07-01

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DOI：10.1109/TNSE.2021.3095040

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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.

Keywords:

Task analysis

Distributed computing

Encoding

Optimization

Computational modeling

Heterogeneous networks

Resource management

Coded distributed computing

heterogeneous computing cluster

batch-processing

asymptotic optimality

latency

On Batch-Processing Based Coded Computing for Heterogeneous Distributed Computing Systems

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