标题:DISWOP: A Novel Scheduling Algorithm for Data-Intensive Workflow Optimizations
作者:Yuyu YUAN;Chuanyi LIU;Jie CHENG;Xiaoliang WANG
通讯作者:Liu, C
作者机构:[Yuan, Y] Software School, Beijing University of Posts and Telecommunications, Beijing, China, Key Laboratory of Trustworthy Distributed Computing and 更多
来源:IEICE transactions on information and systems
出版年:2012
卷:E95D
期:7
页码:1839-1846
DOI:10.1587/transinf.E95.D.1839
关键词:workflow optimization;task clustering;process expression;differential evolution algorithm
摘要:Execution performance is critical for large-scale and data-intensive 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.
收录类别:EI;SCOPUS;SCIE
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863495083&doi=10.1587%2ftransinf.E95.D.1839&partnerID=40&md5=1220c651c1128b9b8970110818cfca07
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