Abstract
In this paper, we consider managing service performance starting from the composition time, aiming to reduce the risk of execution failures during service composition. We use ARIMA to predict workloads of the services at the time when they are likely to be invoked and subsequently predict the response time and chances that the requests for accessing the services may be declined due to admission control. The in-depth analysis can help avoid timing failures during service execution. However, these analyses may incur overhead and we introduce a two-phase composition algorithm to reduce the potential overhead. Our system also considers continuous monitoring and service recomposition to greatly increase the probability of completing the service execution within the deadline. Experimental results show that our service management approach can greatly improve the success rate for meeting the deadline.
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References
Zeng, L., Benatallah, B., Ngu, A.H.H., Dumas, M., Kalagnanam, J., Chang, H.: QoS-aware middleware for web services composition. IEEE Trans. Software Eng. 30(5), 311–327 (2004)
Dai, Y., Yang, L., Zhang, B.: Self-healing web service composition based on performance prediction. J. Comput. Sci. Technol. 24(2), 250–261 (2009)
Yan, Y., Poizat, P., Zhao, L.: Repair vs. recomposition for broken service compositions. In: Maglio, P.P., Weske, M., Yang, J., Fantinato, M. (eds.) ICSOC 2010. LNCS, vol. 6470, pp. 152–166. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-17358-5_11
Ma, H., Bastani, F., Yen, I.-L., Mei, H.: QoS-driven service composition with reconfigurable services. IEEE Trans. Serv. Comput. 6(1), 20–34 (2011)
Bi, J., Zhu, Z., Tian, R., Wang, Q.: Dynamic provisioning modeling for virtualized multi-tier applications in cloud data center. In: IEEE Cloud (2010)
Calheiros, R.N., Ranjany, R., Buyya, R.: Virtual machine provisioning based on analytical performance and QoS in cloud computing environments. In: International Conference on Parallel Processing (2011)
Nan, X., He, Y., Guan, L.: Optimal resource allocation for multimedia cloud in priority service scheme. In: IEEE International Symposium on Circuits and Systems (2012)
Chen, X., Mohapatra, P., Chen, H.: An admission control scheme for predictable server response time for Web accesses. In: WWW10. Citeseer (2001)
D’Ambrogio, A., Bocciarelli, P.: A Model-driven approach to describe and predict the performance of composite services. In: WOSP (2007)
Van Hoecke, S., Verdickt, T., Dhoedt, B., Gielen, F., Demeester, P.: Modelling the performance of the Web Service platform using layered queueing networks. In: SAVCBS (2005)
Wu, Q., Zhang, M., Zheng, R., Lou, Y., Wei, W.: A QoS-satisfied prediction model for cloud-service composition based on a hidden markov model. Math. Probl. Eng. Article ID 387083, 7 p. (2013)
Ye, Z., Mistry, S., Bouguettaya, A.: Long-term-aware cloud service composition using multivariate time series analysis. IEEE Trans. Serv. Comput. 9(3), 382–393 (2016)
Hyndman, R.J., Athanasopoulos, G.: Forecasting, Principles and Practice, 2nd edn. Otexts, Melbourne (2018)
Reiss, C., Wilkes, J., Hellerstein, J.: Google, 17 November 2014. https://drive.google.com/file/d/0B5g07T_gRDg9Z0lsSTEtTWtpOW8/view. Accessed 2016
Ye, Y., Yen, I.-L., Xiao, L., Thuraisingham, B.: Secure, highly available, and high performance peer-to-peer storage systems. In: IEEE (2008)
Zhang, H., Goel, A., Govindan, R.: An empirical evaluation of internet latency expansion. ACM SIGCOMM Comput. Commun. Rev. 35(1), 93–97 (2005)
Moussa, H., Gao, T., Yen, I.-L., Bastani, F., Jeng, J.-J.: Toward effective service composition for real-time SOA-based systems. SOCA 4, 17–31 (2010)
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Moussa, H., Yen, IL., Bastani, F., Dong, Y., He, W. (2019). Toward Better Service Performance Management via Workload Prediction. In: Ferreira, J., Musaev, A., Zhang, LJ. (eds) Services Computing – SCC 2019. SCC 2019. Lecture Notes in Computer Science(), vol 11515. Springer, Cham. https://doi.org/10.1007/978-3-030-23554-3_7
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DOI: https://doi.org/10.1007/978-3-030-23554-3_7
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