Policy-Aware Optimization of Parallel Execution of Composite Services

Mai Xuan Trang; Yohei Murakami; Toru Ishida

doi:10.1109/SCC.2015.24

Policy-Aware Optimization of Parallel Execution of Composite Services

Mai Xuan Trang, Yohei Murakami, Toru Ishida

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Parallel execution and cloud technologies are the keys to speed-up service invocation when processing large-scale data. In SOA, service providers normally employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance improvement, service users need to adapt to parallel execution policies of the services. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency we need to optimize the degree of parallelism (DOP) of the composite services by considering policies of all atomic services. We propose a model that embeds service policies into formulae to calculate composite service performance. From the calculation, we predict the optimal DOP for the composite service. Extensive experiments are conducted on real-world translation services. The results show that our proposed model has good prediction accuracy in identifying the optimal DOPs. Our model correctly predicts the optimal DOP in most cases.

Original language	English
Title of host publication	Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015
Editors	Wu Chou, Paul P. Maglio, Incheon Paik
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	106-113
Number of pages	8
ISBN (Electronic)	9781467372817
DOIs	https://doi.org/10.1109/SCC.2015.24
Publication status	Published - 2015 Aug 17
Externally published	Yes
Event	IEEE International Conference on Services Computing, SCC 2015 - New York, United States Duration: 2015 Jun 27 → 2015 Jul 2

Publication series

Name	Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015

Conference

Conference	IEEE International Conference on Services Computing, SCC 2015
Country/Territory	United States
City	New York
Period	15/6/27 → 15/7/2

Keywords

Big Data
Parallel Execution
Service Composition
Service Policy

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications
Computer Science Applications

Access to Document

10.1109/SCC.2015.24

Cite this

Trang, M. X., Murakami, Y., & Ishida, T. (2015). Policy-Aware Optimization of Parallel Execution of Composite Services. In W. Chou, P. P. Maglio, & I. Paik (Eds.), Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015 (pp. 106-113). [7207342] (Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCC.2015.24

Policy-Aware Optimization of Parallel Execution of Composite Services. / Trang, Mai Xuan; Murakami, Yohei; Ishida, Toru.

Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015. ed. / Wu Chou; Paul P. Maglio; Incheon Paik. Institute of Electrical and Electronics Engineers Inc., 2015. p. 106-113 7207342 (Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Trang, MX, Murakami, Y & Ishida, T 2015, Policy-Aware Optimization of Parallel Execution of Composite Services. in W Chou, PP Maglio & I Paik (eds), Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015., 7207342, Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015, Institute of Electrical and Electronics Engineers Inc., pp. 106-113, IEEE International Conference on Services Computing, SCC 2015, New York, United States, 15/6/27. https://doi.org/10.1109/SCC.2015.24

Trang MX, Murakami Y, Ishida T. Policy-Aware Optimization of Parallel Execution of Composite Services. In Chou W, Maglio PP, Paik I, editors, Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 106-113. 7207342. (Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015). doi: 10.1109/SCC.2015.24

Trang, Mai Xuan ; Murakami, Yohei ; Ishida, Toru. / Policy-Aware Optimization of Parallel Execution of Composite Services. Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015. editor / Wu Chou ; Paul P. Maglio ; Incheon Paik. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 106-113 (Proceedings - 2015 IEEE International Conference on Services Computing, SCC 2015).

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title = "Policy-Aware Optimization of Parallel Execution of Composite Services",

abstract = "Parallel execution and cloud technologies are the keys to speed-up service invocation when processing large-scale data. In SOA, service providers normally employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance improvement, service users need to adapt to parallel execution policies of the services. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency we need to optimize the degree of parallelism (DOP) of the composite services by considering policies of all atomic services. We propose a model that embeds service policies into formulae to calculate composite service performance. From the calculation, we predict the optimal DOP for the composite service. Extensive experiments are conducted on real-world translation services. The results show that our proposed model has good prediction accuracy in identifying the optimal DOPs. Our model correctly predicts the optimal DOP in most cases.",

keywords = "Big Data, Parallel Execution, Service Composition, Service Policy",

author = "Trang, {Mai Xuan} and Yohei Murakami and Toru Ishida",

note = "Funding Information: This research was partly supported by a Grant-in-Aid for Scientific Research (S) (24220002, 2012-2016) from Japan Society for Promotion of Science (JSPS). Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Conference on Services Computing, SCC 2015 ; Conference date: 27-06-2015 Through 02-07-2015",

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AU - Murakami, Yohei

AU - Ishida, Toru

N1 - Funding Information: This research was partly supported by a Grant-in-Aid for Scientific Research (S) (24220002, 2012-2016) from Japan Society for Promotion of Science (JSPS). Publisher Copyright: © 2015 IEEE.

PY - 2015/8/17

Y1 - 2015/8/17

N2 - Parallel execution and cloud technologies are the keys to speed-up service invocation when processing large-scale data. In SOA, service providers normally employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance improvement, service users need to adapt to parallel execution policies of the services. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency we need to optimize the degree of parallelism (DOP) of the composite services by considering policies of all atomic services. We propose a model that embeds service policies into formulae to calculate composite service performance. From the calculation, we predict the optimal DOP for the composite service. Extensive experiments are conducted on real-world translation services. The results show that our proposed model has good prediction accuracy in identifying the optimal DOPs. Our model correctly predicts the optimal DOP in most cases.

AB - Parallel execution and cloud technologies are the keys to speed-up service invocation when processing large-scale data. In SOA, service providers normally employ policies to limit parallel execution of the services based on arbitrary decisions. In order to attain optimal performance improvement, service users need to adapt to parallel execution policies of the services. A composite service is a combination of several atomic services provided by various providers. To use parallel execution for greater composite service efficiency we need to optimize the degree of parallelism (DOP) of the composite services by considering policies of all atomic services. We propose a model that embeds service policies into formulae to calculate composite service performance. From the calculation, we predict the optimal DOP for the composite service. Extensive experiments are conducted on real-world translation services. The results show that our proposed model has good prediction accuracy in identifying the optimal DOPs. Our model correctly predicts the optimal DOP in most cases.

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KW - Service Composition

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Policy-Aware Optimization of Parallel Execution of Composite Services

Abstract

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Conference

Keywords

ASJC Scopus subject areas

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