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Trustworthy Web services provisioning for differentiated customer services

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Abstract

With the number of e-Business applications dramatically increasing, a service level agreement (SLA) will play an important part in Web services. The SLA is a combination of several quality of services (QoS), such as security, performance, and availability, agreed between a customer and a service provider. Most existing research addresses only one of these QoS metrics. Furthermore, in the case of the response time defined as one of QoS metrics for performance, only the average time to process and complete a job is typically used. Moreover, customer requests often need to be distinguished, with different request characteristics and customer’s different service requirements.

In this paper, we consider a set of computer resources used by a service broker to host enterprise applications for two classes of differentiated customer services subject to a service level agreement. We study three QoS metrics, namely, trustworthiness, a percentile response time, and availability. The percentile response time metric defines a value below which the end-to-end response time has to be for a given percent of time. We present an approach for resource optimization in such an environment that minimizes the total cost of computer resources while satisfying all these three QoS metrics in a trust-based resource provisioning problem which typically arises in Web services. We formulate the trust-based resource provisioning problem as an optimization problem under SLA constraints, and then solve it using an efficient numerical procedure.

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References

  1. Azzedin, F., & Maheswaran, M. (2002). Evolving and managing trust in Grid computing systems. In Proc. of the IEEE Canadian conf. on electrical computing engineering (CCECE ’02). IEEE, May 2002.

  2. Bouillet, E., Mitra, D., & Ramakrishnan, K. (2002). The structure and management of service level agreements in networks. IEEE Journal on Selected Areas in Communications, 20(4), 691–699.

    Article  Google Scholar 

  3. Brown, A., & Patterson, D. (2000). Towards availability benchmarks: A case study of software RAID systems. In Proceedings of 2000 USENIX annual technical conference. USENIX, June 2000.

  4. Chandra, A., Gong, W., & Shenoy, P. (2003). Dynamic resource allocation for shared data centers using online measurements. In Proceedings of eleventh international conference on quality of service (IWQoSC 2003), June 2003.

  5. Chang, J. Processor performance, Update 1. In SQL-Server-Performance.com.

  6. Chassot, C., Garcia, F., Auriol, G., Lozes, A., Lochin, E., & Anelli, P. (2002). Performance analysis for an IP differentiated services network. In Proceedings of IEEE international conference on communication (ICC’02) (pp. 976–980).

  7. CISCO, Increasing network availability. http://www.cisco.com/warp/public/779/largeent/learn/technologies/ina/IncreasingNetworkAvailability-Abstract.pdf.

  8. CISCO, Service level management: Best practice. http://www.cisco.com/en/US/tech/tk869/tk769.

  9. Daduna, H. (1984). Burke’s theorem on passage times in Gordon-Newell networks. Advances in Applied Probability, 16(4), 867–886.

    Article  Google Scholar 

  10. Graf, U. (2004). Applied Laplace transforms and z-transforms for scientists and engineers. Basel: Birkhauser.

    Google Scholar 

  11. Hennessy, J. (1999). The future of systems research. IEEE Computer, 32(8), 27–33.

    Google Scholar 

  12. Jurca, R., & Faltings, B. (2005). Reputation-based service level agreements for Web services. In Third international conference on service oriented computing (ICSOC 2005). Amsterdam, The Netherlands, December 2005.

  13. Kamvar, S. D., Schlosser, M. T., & Garcia-Molina, H. (2003). EignRep: Reputation management in P2P networks. In Proceedings of the World-Wide Web conference.

  14. Levy, R., Nagarajarao, J., Pacifici, G., Spreitzer, M., Tantawi, A., & Youssef, A. (2003). Performance management for cluster based Web services. In The 8th IFIP/IEEE international symposium on integrated network management (IM2003). March 2003.

  15. Martin, J., & Nilsson, A. (2002). On service level agreements for IP networks. In IEEE INFOCOM, June 2002.

  16. Menasce, D. (2002). QoS issues in Web services. IEEE Internet Computing, 6(4), 72–75.

    Article  Google Scholar 

  17. Menasce, D. (2004). Response-time analysis of composite Web services. IEEE Internet Computing, 8(1), 90–92.

    Article  Google Scholar 

  18. Menasce, D., & Bennani, M. (2003). On the use of performance models to design self-managing computer systems. In Proceedings of the 2003 computer measurement group conference. IEEE, December 2003.

  19. Menasce, D., & Casalicchio, E. (2004). A framework for resource allocation in grid computing. In Proceedings of the 12th IEEE international symposium on modeling, analysis, and simulation of computer and telecommunications systems (MASCOTS’04) (pp. 259–267). IEEE, October 2004.

  20. Nabrzysbi, J., Schopf, J., & Weglarz, J. (2004). Grid resource management. Boston: Kluwer Academic.

    Google Scholar 

  21. Osogami, T., Wierman, A., Harchol-Balter, M., & Scheller-Wolf, A. (2003). How many servers are best in a dual-priority fcfs system? (CMU Technical Report: CMU-CS-03-201). Carnegie Mellon University, November 2003.

  22. Vu, L., Hauswirth, M., & Aberer, K. QoS-based service selection and ranking with trust and reputation management (Infoscience’s Technical Report).

  23. Walrand, J., & Varaiya, P. (1980). Sojourn times and the overtaking condition in Jacksonian networks. Advances in Applied Probability, 12, 1000–1018.

    Article  Google Scholar 

  24. Wickramage, N., & Weerawarana, S. (2005). A benchmark for Web service frameworks. In Proceedings of the 2005 IEEE international conference on service computing (pp. 233–242). IEEE, July 2005.

  25. Xiong, K., & Perros, H. (2006). Computer resource optimization for differential customer services. In Proceedings of the 14th IEEE international symposium on modeling, analysis, and simulation of computer and telecommunication systems (MASCOTS 2006). IEEE, September 2006.

  26. Zhang, Q., Yu, T., & Irwin, K. (2004). A classification scheme for trust functions in reputation-based trust management. In International workshop on trust, security, and reputation on the semantic web. Hiroshima, November 2004.

  27. Ziegler, C., & Lausen, G. (2002). Spreading activation models for trust propagation. In IEEE international conference on e-technology, e-commerce, and e-service (EEE ’04), April 2002.

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Authors and Affiliations

  1. Department of Computer Science, Texas A&M University, Commerce, TX, 75429, USA

    Kaiqi Xiong

  2. Department of Computer Science, North Carolina State University, Raleigh, NC, 27965, USA

    Harry Perros

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  1. Kaiqi Xiong
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  2. Harry Perros
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Correspondence to Kaiqi Xiong.

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Xiong, K., Perros, H. Trustworthy Web services provisioning for differentiated customer services. Telecommun Syst 39, 171–185 (2008). https://doi.org/10.1007/s11235-008-9126-9

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