Workflow refactoring for concurrent task execution

Mingzhong Wang; J Chen; L Zhu

doi:10.1109/CGC.2012.82

Back

Workflow refactoring for concurrent task execution

Conference paper

Open access

Peer reviewed

Workflow refactoring for concurrent task execution

Mingzhong Wang, J Chen and L Zhu

Proceedings of the 2nd International Conference on Cloud and Green Computing and the 2nd International Conference on Social Computing and Its Applications, pp.629-636

2nd International Conference on Cloud and Green Computing and the 2nd International Conference on Social Computing and Its Applications (CGC/SCA 2012), 2012 (Xiangtan, China, 01-Nov-2012–03-Nov-2012)

IEEE Computer Society

2012

DOI: https://doi.org/10.1109/CGC.2012.82

Files and links (2)

pdf

PDF - Published Version209.30 kBDownload View

Published VersionPDF - Published Version Open Access

url

https://doi.org/10.1109/CGC.2012.82View

Published Version

Abstract

processor scheduling

reliability

schedules

scheduling

system performance

transforms

The performance and reliability of workflow execution are highly dependent on the scheduling algorithm. However, existing approaches usually confines the scheduling on the predefined workflow structure, neglecting the possibility that a workflow graph itself may be changeable when certain conditions are satisfied. Therefore, in this paper we propose the concept of graph refactoring which transforms certain types of sequential tasks to run in parallel without changing system's functionality. We first propose a classification of task dependencies in DAG-style workflow graphs as data, strict control, and loose control dependency according to task interaction and user requirements, and identify that previously sequential task ordering in loose control dependency can be scheduled to run in parallel as long as supporting services are trustworthy. Corresponding refactoring algorithms are designed to traverse, restructure, and parallelize loose control dependencies in the graph when the reputations of related executing services are above certain threshold. Experiments and analysis show that graph refactoring can improve the system performance scalably because of concurrent execution of previously sequential tasks. © 2012 IEEE.

Details

Title: Workflow refactoring for concurrent task execution
Authors: Mingzhong Wang (Author) - Beijing Institute of Technology, China
J Chen (Author) - Beijing Institute of Technology, China
L Zhu (Author) - Beijing Institute of Technology, China
Contributors: Jianxun Liu (Editor)
Jinjun Chen (Editor)
Guangdong Xu (Editor)
Publication details: Proceedings of the 2nd International Conference on Cloud and Green Computing and the 2nd International Conference on Social Computing and Its Applications, pp.629-636
Conference details: 2nd International Conference on Cloud and Green Computing and the 2nd International Conference on Social Computing and Its Applications (CGC/SCA 2012), 2012 (Xiangtan, China, 01-Nov-2012–03-Nov-2012)
Publisher: IEEE Computer Society
Date published: 2012
DOI: 10.1109/CGC.2012.82
ISBN: 9780769548647
Copyright note: Copyright © 2012 IEEE. Reproduced here in accordance with the publisher's copyright policy. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Organisation Unit: University of the Sunshine Coast, Queensland; USC Business School - Legacy; School of Science, Technology and Engineering
Language: English
Record Identifier: 99449598202621
Output Type: Conference paper
Research Statement: false

Metrics

43 File views/ downloads

503 Record Views