Service adaptation with probabilistic partial models

Web service composition makes use of existing Web services to build complex business processes. Non-functional requirements are crucial for the Web service composition. In order to satisfy non-functional requirements when composing a Web service, one needs to rely on the estimated quality of the com...

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Main Authors: CHEN, Manman, TAN, Tian Huat, SUN, Jun, WANG, Jingyi, LIU, Yang, SUN, Jing, DONG, Jin Song
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Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/4943
https://ink.library.smu.edu.sg/context/sis_research/article/5946/viewcontent/418701_Print.indd.pdf
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spelling sg-smu-ink.sis_research-59462020-02-27T03:24:20Z Service adaptation with probabilistic partial models CHEN, Manman TAN, Tian Huat SUN, Jun WANG, Jingyi LIU, Yang SUN, Jing DONG, Jin Song Web service composition makes use of existing Web services to build complex business processes. Non-functional requirements are crucial for the Web service composition. In order to satisfy non-functional requirements when composing a Web service, one needs to rely on the estimated quality of the component services. However, estimation is seldom accurate especially in the dynamic environment. Hence, we propose a framework, ADFlow, to monitor and adapt the workflow of the Web service composition when necessary to maximize its ability to satisfy the non-functional requirements automatically. To reduce the monitoring overhead, ADFlow relies on asynchronous monitoring. ADFlow has been implemented and the evaluation has shown the effectiveness and efficiency of our approach. Given a composite service, ADFlow achieves 25 %–32 % of average improvement in the conformance of non-functional requirements, and only incurs 1 %–3 % of overhead with respect to the execution time. 2016-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4943 info:doi/10.1007/978-3-319-47846-3_9 https://ink.library.smu.edu.sg/context/sis_research/article/5946/viewcontent/418701_Print.indd.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Service Composition Component Service Global Constraint Composite Service Guard Condition Programming Languages and Compilers Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Service Composition
Component Service
Global Constraint
Composite Service
Guard Condition
Programming Languages and Compilers
Software Engineering
spellingShingle Service Composition
Component Service
Global Constraint
Composite Service
Guard Condition
Programming Languages and Compilers
Software Engineering
CHEN, Manman
TAN, Tian Huat
SUN, Jun
WANG, Jingyi
LIU, Yang
SUN, Jing
DONG, Jin Song
Service adaptation with probabilistic partial models
description Web service composition makes use of existing Web services to build complex business processes. Non-functional requirements are crucial for the Web service composition. In order to satisfy non-functional requirements when composing a Web service, one needs to rely on the estimated quality of the component services. However, estimation is seldom accurate especially in the dynamic environment. Hence, we propose a framework, ADFlow, to monitor and adapt the workflow of the Web service composition when necessary to maximize its ability to satisfy the non-functional requirements automatically. To reduce the monitoring overhead, ADFlow relies on asynchronous monitoring. ADFlow has been implemented and the evaluation has shown the effectiveness and efficiency of our approach. Given a composite service, ADFlow achieves 25 %–32 % of average improvement in the conformance of non-functional requirements, and only incurs 1 %–3 % of overhead with respect to the execution time.
format text
author CHEN, Manman
TAN, Tian Huat
SUN, Jun
WANG, Jingyi
LIU, Yang
SUN, Jing
DONG, Jin Song
author_facet CHEN, Manman
TAN, Tian Huat
SUN, Jun
WANG, Jingyi
LIU, Yang
SUN, Jing
DONG, Jin Song
author_sort CHEN, Manman
title Service adaptation with probabilistic partial models
title_short Service adaptation with probabilistic partial models
title_full Service adaptation with probabilistic partial models
title_fullStr Service adaptation with probabilistic partial models
title_full_unstemmed Service adaptation with probabilistic partial models
title_sort service adaptation with probabilistic partial models
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/4943
https://ink.library.smu.edu.sg/context/sis_research/article/5946/viewcontent/418701_Print.indd.pdf
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