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Publisher: IEEE
Languages: English
Types: Other
Subjects:
Increase emphasis on Quality of Service and highly changing environments make management of composite services a time consuming and complicated task. Adaptation approaches aim to mitigate the management problem by adjusting composite services to the environment conditions, maintaining functional and quality levels, and reducing human intervention. This paper presents an adaptation approach that implements self-optimization based on fuzzy logic. The proposed optimization model performs service selection based on the analysis of historical and real QoS data, gathered at different stages during the execution of composite services. The use of fuzzy inference systems enables the evaluation of the measured QoS values, helps deciding whether adaptation is needed or not, and how to perform service selection. Experimental results show significant improvements in the global QoS of the use case scenario, providing reductions up to 20.5% in response time, 33.4% in cost and 31.2% in energy consumption.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] W3C Working Group. (2004, May, 2012). Web Services Architecture. Available: http://www.w3.org/TR/ws-arch/
    • [2] S. Dustdar and W. Schreiner, "A survey on web services composition," International Journal of Web and Grid Services, vol. 1, pp. 1-30, 2005.
    • [3] D. Ardagna and R. Mirandola, "Per-flow optimal service selection for Web services based processes," Journal of Systems and Software, vol. 83, pp. 1512-1523, 2010.
    • [4] W3C Working Group. (2003, July 2010). QoS for Web Services: Requirements and Possible Approaches. Available: http://www.w3c.or.kr/kr-office/TR/2003/ws-qos/
    • [5] S.-Y. Hwang, et al., "A probabilistic approach to modeling and estimating the QoS of web-services-based workflows," Information Sciences, vol. 177, pp. 5484-5503, 2007.
    • [6] J. Cardoso, et al., "Quality of service for workflows and Web service processes," Web Semantics: Science, Services and Agents on the World Wide Web, vol. 1, pp. 281-308, 2004.
    • [7] B. H. Cheng, et al., "Software Engineering for Self-Adaptive Systems: A Research Roadmap," Software Engineering for SelfAdaptive Systems, Lecture Notes In Computer Science, vol. 5525, pp. 1-26 2009.
    • [8] L. A. Zadeh, "The role of fuzzy logic in modeling, identification and control," Modeling, Identification and Control (MIC), vol. 15, pp. 191-203, 1994.
    • [9] P. Châtel, et al., "QoS-based Late-Binding of Service Invocations in Adaptive Business Processes," in Proceedings of the 2010 IEEE International Conference on Web Services, Miami, USA, 2010, pp. 227-234.
    • [10] V. Cardellini, et al., "MOSES: A Framework for QoS Driven Runtime Adaptation of Service-Oriented Systems," Software Engineering, IEEE Transactions on, vol. PP, 2011.
    • [11] L. Wenjuan, et al., "A framework to improve adaptability in web service composition," in Proceedings of the 2nd International Conference on Computer Engineering and Technology (ICCET), Chengdu, China, 2010.
    • [12] A. Erradi, et al., "Policy-driven middleware for self-adaptation of web services compositions," in Proceedings of the ACM/IFIP/USENIX 2006 International Conference on Middleware, Melbourne, Australia, 2006, pp. 62-80.
    • [13] D. Bianculli, et al., "Automated Dynamic Maintenance of Composite Services Based on Service Reputation," in Proceedings of the 5th international conference on Service-Oriented Computing (ICSOC), Vienna, Austria, 2007, pp. 449-455.
    • [14] S. Dustdar, et al., "A roadmap towards sustainable self-aware service systems," in Proceedings of the 2010 ICSE Workshop on Software Engineering for Adaptive and Self-Managing Systems, Cape Town, South Africa, 2010, pp. 10-19.
    • [15] WS-Diamond Team, "WS-DIAMOND: Web ServicesDiAgnosability, MONitoring and Diagnosis," MIT press, pp. 213- 239, 2009.
    • [16] M. Salehie and L. Tahvildari, "Self-adaptive software: Landscape and research challenges," ACM Transactions on Autonomous and Adaptive Systems, vol. 4, pp. 1-42, 2009.
    • [17] M. P. Papazoglou, et al., "Service-Oriented Computing: A Research Roadmap," International Journal of Cooperative Information Systems, vol. 17, pp. 223-255, 2008.
    • [18] A. C. Huang and P. Steenkiste, "Building Self-Configuring Services Using Service-Specific Knowledge," in Proceedings of the 13th IEEE International Symposium on High Performance Distributed Computing, 2004, pp. 45-54.
    • [19] L. A. Zadeh, "Fuzzy sets," Information and Control, vol. 8, pp. 338- 353, 1965.
    • [20] Li-Xin Wang, A course in fuzzy systems and control: Prentice Hall, 1997.
    • [21] L. Zeng, et al., "QoS-Aware Middleware for Web Services Composition," IEEE Transactions on Software Engineering, vol. 30, pp. 311-327, 2004.
    • [22] Y. Dai, et al., "QoS-Driven Self-Healing Web Service Composition Based on Performance Prediction," Journal of Computer Science and Technology, vol. 24, pp. 250-261, March 2009.
    • [23] R. Buyya, et al., "Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges," in Proceedings of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications, las Vegas, USA, 2010.
    • [24] Y. Ying, et al., "A Self-healing composite Web service model," in Proceedings of the IEEE Asia-Pacific Services Computing Conference (APSCC), Biopolis, Singapore, 2009, pp. 307-312.
    • [25] J. Kaplan, et al., "Revolutionizing Data Center Energy Efficiency," McKinsey,July 2009.
    • [26] A. Erradi, et al., "WS-Policy based Monitoring of Composite Web Services," in Proceedings of the 5th IEEE European Conference on Web Services, Halle, Germany, 2007, pp. 99-108.
    • [27] Energy Star, "Computer Servers Product List - Families," August, 2012.
    • [28] OASIS. (2007, June 2010). Web Services Business Process Execution Language Version 2.0. Available: http://docs.oasisopen.org/wsbpel/2.0/OS/wsbpel-v2.0-OS.html
    • [29] G. Wu, et al., "Towards self-healing Web Services Composition," in Proceedings of the First Asia-Pacific Symposium on Internetware, Beijing, China, 2009.
    • [30] D. Ardagna, et al., "A Service-Based Framework for Flexible Business Processes," IEEE Software, vol. 28, pp. 61-67, 2011.
    • [31] A. Erradi and P. Maheshwari, "Dynamic Binding Framework for Adaptive Web Services," in Proceedings of the 2008 Third International Conference on Internet and Web Applications and Services, Athens, Greece, 2008, pp. 162-167.
    • [32] G. Canfora, et al., "A framework for QoS-aware binding and rebinding of composite web services," The Journal of Systems and Software, vol. 81, pp. 1754-1769, 2008.
    • [33] R. Calinescu, et al., "Dynamic QoS Management and Optimization in Service-Based Systems," IEEE Transactions on Software Engineering, vol. 37, pp. 387-409, 2011.
    • [34] D. Ardagna, et al., "PAWS: A Framework for Executing Adaptive Web-Service Processes," IEEE Software, vol. 24, pp. 39-46, 2007.
    • [35] B. Pernici and S. H. Siadat, "Selection of Service Adaptation Strategies Based on Fuzzy Logic," in Proceedings of the 2011 IEEE World Congress on Services (SERVICES), Washington DC, USA, 2011, pp. 99-106.
    • [36] C. Kuo-Ming, et al., "Fuzzy matchmaking for Web services," in Proceedings of the 19th International Conference on Advanced Information Networking and Applications (AINA), Tamkang University, Taiwan, 2005, pp. 721-726 vol.2.
    • [37] P. Wang, et al., "A Fuzzy Model for Selection of QoS-Aware Web Services," in Proceedings of the IEEE International Conference on eBusiness Engineering (ICEBE), Shanghai, China, 2006, pp. 585-593.
    • [38] H. Pfeffer, et al., "A Fuzzy Logic Based Model for Representing and Evaluating Service Composition Properties," in Proceedings of the 3rd International Conference on Systems and Networks Communications (ICSNC), Sliema, Malta, 2008, pp. 335-342.
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