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Modeling dynamic recovery strategy for composite web services execution

Authors:

Rafael Angarita,

Yudith CardinaleAuthors Info & Claims

World Wide Web, Volume 19, Issue 1

Pages 89 - 109

https://doi.org/10.1007/s11280-015-0329-1

Published: 01 January 2016 Publication History

Abstract

During the execution of Composite Web Services (CWS), a component Web Service (WS) can fail and can be repaired with strategies such WS retry, substitution, compensation, roll-back, replication, or checkpointing. Each strategy behaves differently on different scenarios, impacting the CWS QoS. We propose a non intrusive dynamic fault tolerant model that analyses several levels of information: environment state, execution state, and QoS criteria, to dynamically decide the best recovery strategy when a failure occurs. We present an experimental study to evaluate the model and determine the impact on QoS parameters of different recovery strategies; and evaluate the intrusiveness of our strategy during the normal execution of CWSs.

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Cited By

Abdulrazak BCodjo JPaul S(2022)Self-healing Approach for IoT Architecture: AMI PlatformParticipative Urban Health and Healthy Aging in the Age of AI10.1007/978-3-031-09593-1_1(3-17)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-09593-1_1
Yu DZhang LLiu CZhou RXu D(2020)Automatic Web service composition driven by keyword queryWorld Wide Web10.1007/s11280-019-00742-523:3(1665-1692)Online publication date: 7-Feb-2020
https://dl.acm.org/doi/10.1007/s11280-019-00742-5
ElGhondakly RMoussa SBadr N(2020)Handling Faults in Service Oriented Computing: A Comprehensive StudyComputational Science and Its Applications – ICCSA 202010.1007/978-3-030-58811-3_67(947-959)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-58811-3_67
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Modeling dynamic recovery strategy for composite web services execution

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Information

Published In

cover image World Wide Web

World Wide Web Volume 19, Issue 1

January 2016

170 pages

ISSN:1386-145X

Issue’s Table of Contents

Copyright © Copyright © 2016 Springer Science+Business Media New York.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 January 2016

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Cited By

Abdulrazak BCodjo JPaul S(2022)Self-healing Approach for IoT Architecture: AMI PlatformParticipative Urban Health and Healthy Aging in the Age of AI10.1007/978-3-031-09593-1_1(3-17)Online publication date: 27-Jun-2022
https://dl.acm.org/doi/10.1007/978-3-031-09593-1_1
Yu DZhang LLiu CZhou RXu D(2020)Automatic Web service composition driven by keyword queryWorld Wide Web10.1007/s11280-019-00742-523:3(1665-1692)Online publication date: 7-Feb-2020
https://dl.acm.org/doi/10.1007/s11280-019-00742-5
ElGhondakly RMoussa SBadr N(2020)Handling Faults in Service Oriented Computing: A Comprehensive StudyComputational Science and Its Applications – ICCSA 202010.1007/978-3-030-58811-3_67(947-959)Online publication date: 1-Jul-2020
https://dl.acm.org/doi/10.1007/978-3-030-58811-3_67
Kahlon NChahal KNarang S(2019)A weakest link-driven global QoS adjustment approach for optimizing the execution of a composite web serviceKnowledge and Information Systems10.1007/s10115-019-01344-361:3(1431-1455)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.1007/s10115-019-01344-3
Zhang JZhou ASun QWang SYang F(2018)Overview on Fault Tolerance Strategies of Composite Service in Service ComputingWireless Communications & Mobile Computing10.1155/2018/97875032018Online publication date: 19-Jun-2018
https://dl.acm.org/doi/10.1155/2018/9787503
Chen LLiu LShang J(2016)Fault Tolerance for Web Service Based on Component Importance in Service NetworksProceedings of the Fifth International Conference on Network, Communication and Computing10.1145/3033288.3033328(103-109)Online publication date: 17-Dec-2016
https://dl.acm.org/doi/10.1145/3033288.3033328
Angarita RRukoz MManouvrier MCardinale YChbeir RAgrawal RBiskri I(2016)A knowledge-based approach for self-healing service-oriented applicationsProceedings of the 8th International Conference on Management of Digital EcoSystems10.1145/3012071.3012100(1-8)Online publication date: 1-Nov-2016
https://dl.acm.org/doi/10.1145/3012071.3012100

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