BPEL process decomposition approach based on data flow optimization

Yan Long Zhai; Hong Yi Su; Han Zhang; Shou Yi Zhan

BPEL process decomposition approach based on data flow optimization

Yan Long Zhai^*, Hong Yi Su, Han Zhang, Shou Yi Zhan

^*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

As the centralized BPEL process can not provide sufficient supports for the dynamic process management, a BPEL process decomposition approach based on data flow optimization is proposed to support the decentralized coordination. In the approach, a BPEL process is represented as a program flow graph (PFG), and data flow equations are deduced to analyze the data flow information. Moreover, the copy propagation algorithm is extended to optimize the data flow in the PFG, and the BPEL process is partitioned according to the optimized PFG. Experimental results show that, after the decomposition, the response time cost reduces by about 30%-50%, and the computational complexity decreases from O(eⁿ) to O(nⁿ).

Original language	English
Pages (from-to)	24-30
Number of pages	7
Journal	Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)
Volume	37
Issue number	4
Publication status	Published - Apr 2009

Keywords

Data flow analysis
Decentralized coordination
Process decomposition
Service composition

Cite this

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title = "BPEL process decomposition approach based on data flow optimization",

abstract = "As the centralized BPEL process can not provide sufficient supports for the dynamic process management, a BPEL process decomposition approach based on data flow optimization is proposed to support the decentralized coordination. In the approach, a BPEL process is represented as a program flow graph (PFG), and data flow equations are deduced to analyze the data flow information. Moreover, the copy propagation algorithm is extended to optimize the data flow in the PFG, and the BPEL process is partitioned according to the optimized PFG. Experimental results show that, after the decomposition, the response time cost reduces by about 30%-50%, and the computational complexity decreases from O(en) to O(nn).",

keywords = "Data flow analysis, Decentralized coordination, Process decomposition, Service composition",

author = "Zhai, {Yan Long} and Su, {Hong Yi} and Han Zhang and Zhan, {Shou Yi}",

year = "2009",

month = apr,

language = "English",

volume = "37",

pages = "24--30",

journal = "Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)",

issn = "1000-565X",

publisher = "South China University of Technology",

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TY - JOUR

T1 - BPEL process decomposition approach based on data flow optimization

AU - Zhai, Yan Long

AU - Su, Hong Yi

AU - Zhang, Han

AU - Zhan, Shou Yi

PY - 2009/4

Y1 - 2009/4

N2 - As the centralized BPEL process can not provide sufficient supports for the dynamic process management, a BPEL process decomposition approach based on data flow optimization is proposed to support the decentralized coordination. In the approach, a BPEL process is represented as a program flow graph (PFG), and data flow equations are deduced to analyze the data flow information. Moreover, the copy propagation algorithm is extended to optimize the data flow in the PFG, and the BPEL process is partitioned according to the optimized PFG. Experimental results show that, after the decomposition, the response time cost reduces by about 30%-50%, and the computational complexity decreases from O(en) to O(nn).

AB - As the centralized BPEL process can not provide sufficient supports for the dynamic process management, a BPEL process decomposition approach based on data flow optimization is proposed to support the decentralized coordination. In the approach, a BPEL process is represented as a program flow graph (PFG), and data flow equations are deduced to analyze the data flow information. Moreover, the copy propagation algorithm is extended to optimize the data flow in the PFG, and the BPEL process is partitioned according to the optimized PFG. Experimental results show that, after the decomposition, the response time cost reduces by about 30%-50%, and the computational complexity decreases from O(en) to O(nn).

KW - Data flow analysis

KW - Decentralized coordination

KW - Process decomposition

KW - Service composition

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M3 - Article

AN - SCOPUS:66349099395

SN - 1000-565X

VL - 37

SP - 24

EP - 30

JO - Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)

JF - Huanan Ligong Daxue Xuebao/Journal of South China University of Technology (Natural Science)

IS - 4

ER -

BPEL process decomposition approach based on data flow optimization

Abstract

Keywords

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