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

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概要

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• 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.

• 2012-07-01

著者

• CHENG Jie

  School of Computer Science and Technology, ShanDong University

• WANG Xiaoliang

  Software School, Beijing University of Posts and Telecommunications

• YUAN Yuyu

  Software School, Beijing University of Posts and Telecommunications

• LIU Chuanyi

  Software School, Beijing University of Posts and Telecommunications

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