"Endpoint Communication Contention-Aware Cloud Workflow Scheduling" by Quanwang Wu, Meng Chu Zhou et al.
 

Endpoint Communication Contention-Aware Cloud Workflow Scheduling

Document Type

Article

Publication Date

4-1-2022

Abstract

Cloud platforms have recently become a popular target execution environment for numerous workflow applications. Hence, effective workflow scheduling strategies in cloud environments are in high demand. However, existing scheduling algorithms are grounded on an idealized target platform model where virtual machines are fully connected, and all communications can be performed concurrently. A significant aspect neglected by them is endpoint communication contention when executing workflows, which has a large impact on workflow makespan. This article investigates how to incorporate contention awareness into cloud workflow scheduling and proposes a new practical scheduling model. Endpoint communication contention-aware List Scheduling Heuristic (ELSH) is designed to minimize workflow makespan. It uses a novel task ranking property and schedules data communications to communication resources besides scheduling tasks to computing resources. Moreover, a rescheduling technique is employed to improve the schedule. In experiments, ELSH is evaluated against the traditional contention-oblivious list scheduling algorithm, which is adapted to address contention during execution in practice. The experimental results reveal that ELSH performs more efficaciously compared with the adapted traditional ones. Note to Practitioners - This article aims to advance the state of the art for workflow scheduling in clouds by taking into account endpoint communication contention that can occur in practice but has largely been neglected in existing investigations. A scheduling method called Endpoint communication contention-aware List Scheduling Heuristic (ELSH) is then proposed to optimize workflow makespan. Experimental results based on synthetic and realistic workflows show that ELSH performs better than traditional scheduling algorithms that fail to consider endpoint communication contention, especially for the workflow with a large communication-to-computation-cost ratio. The proposed approach can be readily put into use and help cloud service providers to offer their customers high-quality services when executing the latter's workflows.

Identifier

85100848976 (Scopus)

Publication Title

IEEE Transactions on Automation Science and Engineering

External Full Text Location

https://doi.org/10.1109/TASE.2020.3046673

e-ISSN

15583783

ISSN

15455955

First Page

1137

Last Page

1150

Issue

2

Volume

19

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