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Optimized Composite Service Transactions through Execution Results Prediction

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conference contribution
posted on 09.12.2016, 15:16 by J. Xu, Z. Li, H. Chi, M. Wang, C. Guan, Stephan Reiff-Marganiec, H. Shen
Abstract: Traditional web services transaction processing mechanism handle exception by forward recovery and backward recovery. These compensation mechanisms often lead to waste of resources and time. In this paper, we propose a framework for predicting outcomes of service executions as part of service compositions which allows to choose service instances that are likely to lead to a successful result in the first instance and thus reduces the need for invoking costly recovery mechanisms. The framework makes use of watchdogs to maintain an awareness of service availability and a pre-coordinator which has oversight of the whole composite Web service and acts as a control center. An analysis of a scenario shows that we cannot only provide users with a more satisfactory result, but also can reduce the overhead costs of resources and waste.

Funding

The paper is fully supported by a grant from the Fundamental Research Funds for the Central Universities (Project No. 13CX06009A and No. 14CX06007A). This work is a partial result of Jiuyun’s visit to the University of Leicester supported by China Scholarship Council.

History

Citation

2016 IEEE International Conference on Web Services (ICWS), San Francisco, CA, 2016, pp. 690-693.

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Computer Science

Source

IEEE International Conference on Web Services (ICWS) 2016, San Francisco, CA

Version

AM (Accepted Manuscript)

Published in

2016 IEEE International Conference on Web Services (ICWS)

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

isbn

978-1-5090-2676-0;978-1-5090-2675-3

Acceptance date

26/04/2016

Available date

09/12/2016

Publisher version

http://ieeexplore.ieee.org/abstract/document/7558070/

Temporal coverage: start date

27/06/2016

Temporal coverage: end date

02/07/2016

Language

en

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