Web service selection based on response time based on QOS

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Choosing an ideal web benefit among a summary of practically proportional web benefits is still a test problem. For the benefits of the Internet, the proximity of low performing servers, high inactivity or the general poor quality of the administration can turn into lost business, disappointment of the client and lost clients. Existing framework in view of Hidden Markov Models, which also proposes an ideal form for the execution of customer demands. Just calculate the reaction time. In this endeavor we propose three different calculations Ant Colony (- based) Optimization, hereditary calculation and Analytic Algorithm. The method we display may be used to compute and anticipate the behavior of internet services in phrases of costs, accessibility and reaction time could be used to classify administrations quantitatively instead of simply subjectively. Against the rationalization calculation of the province used to organize the reaction time. Hereditary calculation used to distinguish the specific cost of the web benefit and the research calculation used to verify the accessibility of web services. It shows the accessibility and manageability of our strategy by extracting probes of genuine information. The outcomes have proven how our proposed technique can allow the client to consistently choose almost all reliable Web To benefit from considering some measurements, among them, the consistency of the frame and the inconsistency of the reaction time.


  • Keywords


    SOA; Web Services, QoS; Web Provider Ping; Web Provider Routing.

  • References


      [1] V. Cortellessa and V. Grassi, ‘‘Reliability Modeling and Analysisof Service-Oriented Architectures,’’ inTest and Analysis of WebServices. Berlin, Germany: Springer-Verlag, 2007, pp. 339-362.

      [2] G. Stefano, C. Ghezzi, R. Mirandola, and G. Tamburrelli, ‘‘Quality Prediction of Service Compositions through Probabilistic Model Checking,’’ in Proc. 4th Int’l Conf. Quality SoftwareArchitect. Models Architect. 2008, pp. 119-134.

      [3] D.A. Menasce, ‘‘Composing Web Services: A QoS View,’’ IEEEInternetComput. vol. 8, no. 6, pp. 80-90, Nov. 2004. https://doi.org/10.1109/MIC.2004.71.

      [4] H.Zheng, J.Yang, W.Zhao, andA.Bouguettaya, ‘‘QoSAnalysisfor Web Service Compositions Based on Probabilistic QoS,’’ inService-Oriented Computing. Berlin, Germany: Springer-Verlag, 2011, pp. 47-61.

      [5] Z. Zibin and R.L. Michael, ‘‘Collaborative Reliability Predictionof Service-Oriented Systems,’’ inProc. 32nd ACM/IEEE Int’l Conf.Softwa. Eng., Cape Town, Africa, 2010, vol. 1, pp. 35-44.

      [6] R.Perrone, R.Macedo, G.Lima, andV.Lima, a‘‘AnApproachforEstimating Execution Time Probability Distributions of ComponentBased Real-Time Systems,’’J. Universal Comput. Sci., vol.15, no.11,pp. 2142-2165, 2009.

      [7] M. Cristescu and L. Ciovica, ‘‘Estimation of the Reliability ofDistributed Applications,’’Infa. Econ., vol. 14, no. 4, pp. 19-29, 2010.

      [8] D. Zhong, Z. Qi, and X. Xu, ‘‘Reliability Prediction andSensitivity Analysis of WS Composition,’’ inPetri Net: Theoryand Applications, V. Kordic, Ed. Rijeka, Croatia: Intech, 2008, pp. 459-470.

      [9] J. El Haddad, M. Manouvrier, G. Ramirez, and M. Rukoz, ‘‘QoSDrivena Selection of Web Services for Transactional Composition,’’ inProc. IEEE ICWS, 2008, pp. 653-660.

      [10] B. Sami, G. Claude, and P. Olivier, ‘‘Transactional Patterns forReliable Web Services Compositions,’’ inProc. 6th Int’l Conf. WebEng., Palo Alto, CA, USA, 2006, pp. 137-144.

      [11] Y. Tao, Z. Yue, and L. Kwei-Jay, ‘‘Efficient Algorithms for WebServices Selection with End-to-End QoS Constraints,’’ ACMTrans. Web, vol. 1, no. 1, p. 6, May 2007. https://doi.org/10.1145/1232722.1232728.

      [12] Z. Yilei, Z. Zibin, and M.R.Lyua, ‘‘WSPred:ATime-AwarePersonalizedQoS Prediction Framework for Web Services,’’ inProc. IEEE 22nd ISSRE, 2011, pp. 210-219.

      [13] S. Maheswari, ‘‘QoS Based Efficient Web Service Selection, ’Eur.J. Sci. Res., vol. 66, pp. 428-440, 2011.

      [14] C. Leilei, Q. Wang, W. Xu, and L. Zhang, ‘‘Evaluating theSurvivability of SOA Systems Based on HMM,’’ inProc. IEEEInt’l Conf. Web Serv., 2010, pp. 673-675.

      [15] G. Rahnavard, M.S.A. Najjar, and S. Taherifar, ‘‘A Method toEvaluate Web Services Anomaly Detection Using HiddenMarkov Models,’’ inProc. ICCAIE, 2010, pp. 261-265.

      [16] F. Salfner, ‘‘Predicting Failures with Hidden Markov Models,’’ inProc. 5th Eur. Dependable Comput. Conf., 2005, pp. 41-46.

      [17] M. Zaki, A. Ihsaaan, and B. Athman, ‘‘Web Services ReputationAssessment Using a Hidden Markov Model,’’ inProc. 7th Int’lJoint Conf. Serv.-Oriented a Comput. 2009, pp. 576-591.

      [18] W. Ahmed and Y.W. Wu, ‘‘A Survey on Reliability in DistributedSystems,’’J. Comput. Syst. Sci., vol. 79, no. 8, pp. 1243-1255, Dec. 2013. https://doi.org/10.1016/j.jcss.2013.02.006.

      [19] P. Blunsom,Hidden Markov Models,Retrieved May 19, 2006, and 2004.[Online]. Available: www.cs.mu.oz.au/460/2004/materials/hmmtutorial.pdf.

      [20] L. Li, L. Chengfei, and W. Junhu, ‘‘Deriving TransactionalProperties of Composite Web Services,’’ inProc. IEEE ICWS, 2007, pp. 631-638.

      [21] K. Boumhamdi and Z. Jarir, ‘‘A Flexible Approach to ComposeWeb Services in Dynamic Environment,’’Int’l J. Digit. Soc., vol.1, no. 2, pp. 157-163, 2010. https://doi.org/10.20533/ijds.2040.2570.2010.0020.


 

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Article ID: 9485
 
DOI: 10.14419/ijet.v7i1.1.9485




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