DISWOP: A novel scheduling algorithm for data-intensive workflow optimizations

Yuyu Yuan; Chuanyi Liu; Jie Cheng; Xiaoliang Wang

doi:10.1587/transinf.E95.D.1839

DISWOP: A novel scheduling algorithm for data-intensive workflow optimizations

Yuyu Yuan
, Chuanyi Liu^*
, Jie Cheng
, Xiaoliang Wang

^*Corresponding author for this work

Beijing University of Posts and Telecommunications
Ministry of Education of the People's Republic of China
Shandong University

Research output: Contribution to journal › Article › peer-review

Abstract

Execution performance is critical for large-scale and dataintensive workflows. This paper proposes DISWOP, a novel scheduling algorithm for data-intensive workflow optimizations; it consists of three main steps: workflow process generation, task & resource mapping, and task clustering. To evaluate the effectiveness and efficiency of DISWOP, a comparison evaluation of different workflows is conducted a prototype workflow platform. The results show that DISWOP can speed up execution performance by about 1.6-2.3 times depending on the task scale.

Original language	English
Pages (from-to)	1839-1846
Number of pages	8
Journal	IEICE Transactions on Information and Systems
Volume	E95-D
Issue number	7
DOIs	https://doi.org/10.1587/transinf.E95.D.1839
State	Published - Jul 2012
Externally published	Yes

Keywords

Differential Evolution algorithm
Process expression
Task clustering
Workflow optimization

Access to Document

10.1587/transinf.E95.D.1839

Cite this

@article{e697bb181ecc4a83b01b136ac73b24e6,

title = "DISWOP: A novel scheduling algorithm for data-intensive workflow optimizations",

abstract = "Execution performance is critical for large-scale and dataintensive workflows. This paper proposes DISWOP, a novel scheduling algorithm for data-intensive workflow optimizations; it consists of three main steps: workflow process generation, task \& resource mapping, and task clustering. To evaluate the effectiveness and efficiency of DISWOP, a comparison evaluation of different workflows is conducted a prototype workflow platform. The results show that DISWOP can speed up execution performance by about 1.6-2.3 times depending on the task scale.",

keywords = "Differential Evolution algorithm, Process expression, Task clustering, Workflow optimization",

author = "Yuyu Yuan and Chuanyi Liu and Jie Cheng and Xiaoliang Wang",

year = "2012",

month = jul,

doi = "10.1587/transinf.E95.D.1839",

language = "英语",

volume = "E95-D",

pages = "1839--1846",

journal = "IEICE Transactions on Information and Systems",

issn = "0916-8532",

publisher = "Maruzen Co., Ltd/Maruzen Kabushikikaisha",

number = "7",

}

TY - JOUR

T1 - DISWOP

T2 - A novel scheduling algorithm for data-intensive workflow optimizations

AU - Yuan, Yuyu

AU - Liu, Chuanyi

AU - Cheng, Jie

AU - Wang, Xiaoliang

PY - 2012/7

Y1 - 2012/7

N2 - Execution performance is critical for large-scale and dataintensive workflows. This paper proposes DISWOP, a novel scheduling algorithm for data-intensive workflow optimizations; it consists of three main steps: workflow process generation, task & resource mapping, and task clustering. To evaluate the effectiveness and efficiency of DISWOP, a comparison evaluation of different workflows is conducted a prototype workflow platform. The results show that DISWOP can speed up execution performance by about 1.6-2.3 times depending on the task scale.

AB - Execution performance is critical for large-scale and dataintensive workflows. This paper proposes DISWOP, a novel scheduling algorithm for data-intensive workflow optimizations; it consists of three main steps: workflow process generation, task & resource mapping, and task clustering. To evaluate the effectiveness and efficiency of DISWOP, a comparison evaluation of different workflows is conducted a prototype workflow platform. The results show that DISWOP can speed up execution performance by about 1.6-2.3 times depending on the task scale.

KW - Differential Evolution algorithm

KW - Process expression

KW - Task clustering

KW - Workflow optimization

UR - https://www.scopus.com/pages/publications/84863495083

U2 - 10.1587/transinf.E95.D.1839

DO - 10.1587/transinf.E95.D.1839

M3 - 文章

AN - SCOPUS:84863495083

SN - 0916-8532

VL - E95-D

SP - 1839

EP - 1846

JO - IEICE Transactions on Information and Systems

JF - IEICE Transactions on Information and Systems

IS - 7

ER -

DISWOP: A novel scheduling algorithm for data-intensive workflow optimizations

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this