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.
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Yuyu YUAN, Chuanyi LIU, Jie CHENG, Xiaoliang WANG, "DISWOP: A Novel Scheduling Algorithm for Data-Intensive Workflow Optimizations" in IEICE TRANSACTIONS on Information,
vol. E95-D, no. 7, pp. 1839-1846, July 2012, doi: 10.1587/transinf.E95.D.1839.
Abstract: 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.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.E95.D.1839/_p
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@ARTICLE{e95-d_7_1839,
author={Yuyu YUAN, Chuanyi LIU, Jie CHENG, Xiaoliang WANG, },
journal={IEICE TRANSACTIONS on Information},
title={DISWOP: A Novel Scheduling Algorithm for Data-Intensive Workflow Optimizations},
year={2012},
volume={E95-D},
number={7},
pages={1839-1846},
abstract={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.},
keywords={},
doi={10.1587/transinf.E95.D.1839},
ISSN={1745-1361},
month={July},}
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TY - JOUR
TI - DISWOP: A Novel Scheduling Algorithm for Data-Intensive Workflow Optimizations
T2 - IEICE TRANSACTIONS on Information
SP - 1839
EP - 1846
AU - Yuyu YUAN
AU - Chuanyi LIU
AU - Jie CHENG
AU - Xiaoliang WANG
PY - 2012
DO - 10.1587/transinf.E95.D.1839
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E95-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2012
AB - 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.
ER -