DISWOP: A Novel Scheduling Algorithm for Data-Intensive Workflow Optimizations

Yuyu YUAN  Chuanyi LIU  Jie CHENG  Xiaoliang WANG  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E95-D   No.7   pp.1839-1846
Publication Date: 2012/07/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E95.D.1839
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Fundamentals of Information Systems
Keyword: 
workflow optimization,  task clustering,  process expression,  Differential Evolution algorithm,  

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Summary: 
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.