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The Representation and Computation of QoS Preference with Its Applications in Grid Computing Environments

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Abstract

In Grid computing environment, quality of service (QoS) provisioning must be provided to the end users on the basis of their specific requirements. This paper proposes in a first step QoS attributes for Grid applications. In this matter, a mix of quantitative and qualitative parameters have to be considered. In the context, the analytical hierarchy process (AHP) technique [1] is a possible approach to formulate the QoS requirements of the users for Grid services. In order to apply QoS preference to actual application, we introduce a QoS function and a metric for user's satisfaction degrees. These both tools can be used as an evaluation criterion by the user. Subsequently, an algorithm of service selection considering the user's QoS preference is presented. Our empirical studies indicate that the application can reliably select the optimal service for users.

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References

  1. Saaty TL (1980) The analytical hierarchy process. Mc Graw-Hill, New York

    Google Scholar 

  2. Liang Q, Yang Y, Liu L (2007) A service-oriented Grid model with quality of service provision. Inf Control 36(4):401–409

    Google Scholar 

  3. Joutsensaloa J, Luostarinenb K, Siltanenc J et al (2006) Adaptive scheduling method for maximizing revenue in flat pricing scenario. AEU Int J Electron Commun 60(2):159–167

    Article  Google Scholar 

  4. Joutsensalo J, Viinikainen A, Wikstrom M et al (2007) Pricing based adaptive scheduling method for bandwidth allocation. AEUÉ Int J Electron Commun 61(2):118–126

    Article  Google Scholar 

  5. Dai YS, Xie M, Poh KL (2006) Reliability of Grid service systems. Comput Ind Eng 50(1-2):130–147

    Article  Google Scholar 

  6. Liu Y, Ngu AHH, Zeng L (2004) QoS computation and policing in dynamic Web service selection. ACM SIGecom Exchanges 5(5):66–73

    Google Scholar 

  7. Amin K, von Laszewski G, Hategan M et al (2006) An abstraction model for a Grid execution framework. Journal of System Architecture 52(2):73–87

    Article  Google Scholar 

  8. Zeng LZ, Benatallah B (2004) QoS-aware middleware for Web service composition. IEEE Trans Softw Eng 30(5):311–327

    Article  Google Scholar 

  9. Lee H, Chung K, Chin S et al (2005) A resource management and fault tolerance services in Grid computing. Journal of Parallel and Distributed Computing 65(11):1305–1317

    Article  Google Scholar 

  10. Chen YP, Li ZZh, Tang YZh (2006) A method satisfying Markov process of Web service composition under incomplete constrains. Chinese Journal of Computers 29(7):1076–1084

    Google Scholar 

  11. Sunjae L, Wonchul S, Dongwoo K et al (2007) A framework for supporting bottom-up ontology evolution for discovery and description of Grid services. Expert Systems with Applications 32(2):376–385

    Article  Google Scholar 

  12. Mastroianni C, Talia D, Verta O (2005) A super-peer model for resource discovery services in large-scale Grids. Future Generation Computer Systems 21(8):1235–1248

    Article  Google Scholar 

  13. Malhan MS, Shah RN (2006) Dynamic system activity profile forecasting for improved resource selection in quality of service based Grid computing model[C]. Proceeding of the 1st International Conference on Communication Systems Software and Middleware, IEEE press 1(2):308–312

    Google Scholar 

  14. Deora V, Shao J, Gray WA, et al. Supporting QoS based selection in service oriented architecture[C]. Proceeding of International Conference on Next Generation Web Services Practices, IEEE COMPUTER SOC, 2006:117 – 123.

  15. Mei Lin, Zhangxi Lin (2006) A cost-effective critical path approach for service priority selections in Grid computing economy. Decision Support Systems 4(3):1628–1640

    Google Scholar 

  16. Doulamis N, Doulamis A, Litke A et al (2007) Adjusted fair scheduling and non-linear workload prediction for QoS guarantees in Grid computing[J]. Comput Commun 30(3):499–515

    Article  Google Scholar 

  17. Z. SH. Xu. The decision making method of Indefinite multi-objective and its application[M]. Beijing: Tsinghua University Publishing House, 2004.

  18. Guo ChX, Guo HH (2005) Approach of multiple-attribute group decision making. Journal of Systems Engineering and Electronics 27(1):63–65

    Google Scholar 

  19. Chinagrid.Introduce.http://chinagrid.hust.edu.cn/index.php,Last visited:Dec,2008.

Download references

Acknowledgment

We will say thanks to our friends and classmates, they gave us many good ideas and suggestions, we cannot finish the work without their help. At the same time, thanks a lot for the support of National Natural Science Foundation of China (no. 60803123 and no. 60873193) and Science Research Projects of Fujian University of Technology (no. GY-Z09009).

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Authors and Affiliations

  1. Department of Computer and Information Science, Fujian University of Technology, Fuzhou, 350108, China

    Quan Liang

  2. Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China

    Yuanzhuo Wang

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  1. Quan Liang
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  2. Yuanzhuo Wang
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Corresponding author

Correspondence to Quan Liang.

Additional information

Foundation: National Natural Science Foundation of China (no. 60803123 and no. 60873193); Science Research Projects of Fujian University of Technology (no. GY-Z09009).

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Liang, Q., Wang, Y. The Representation and Computation of QoS Preference with Its Applications in Grid Computing Environments. Ann. Telecommun. 65, 705–712 (2010). https://doi.org/10.1007/s12243-010-0193-z

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  • DOI: https://doi.org/10.1007/s12243-010-0193-z

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