Workload prediction using ARIMA model and its impact on cloud applications' QoS

IEEE Transactions on Cloud Computing

Volumn 3, Issue 4, 2015, Pages 449-458

  Calheiros, Rodrigo N ^a   Masoumi, Enayat ^a   Ranjan, Rajiv ^b   Buyya, Rajkumar ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b CSIRO   (Australia)

Author keywords

ARIMA; Cloud computing; Workload prediction

Indexed keywords

APPLICATION PROGRAMS; CLOUD COMPUTING; COST EFFECTIVENESS; EFFICIENCY; FORECASTING; QUALITY OF SERVICE; WEB SERVICES;

ARIMA; AUTOREGRESSIVE INTEGRATED MOVING AVERAGE MODELS; CLOUD APPLICATIONS; COMPETITIVE MARKETS; DESKTOP APPLICATIONS; DYNAMIC PROVISIONING; RESOURCE UTILIZATIONS; WORKLOAD PREDICTIONS;

SOFTWARE AS A SERVICE (SAAS);

EID: 84951964638     PISSN: None     EISSN: 21687161     Source Type: Journal    
DOI: 10.1109/TCC.2014.2350475     Document Type: Article

References (24)

1. R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg, and I. Brandic, "Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility", Future Generation Comput. Syst., vol. 25, no. 6, pp. 599-616, Jun. 2009.
2. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, "A view of cloud computing", Commun. ACM, vol. 53, no. 4, pp. 50-58, Apr. 2010.
3. Q. Zhu and G. Agrawal, "Resource provisioning with budget constraints for adaptive applications in cloud environments", in Proc. 19th ACM Int. Symp. High Perform. Distrib. Comput., Jun. 2010, pp. 304-307.
4. N. Bonvin, T. G. Papaioannou, and K. Aberer, "Autonomic SLA-driven provisioning for cloud applications", in Proc. 11th Int. Symp. Cluster, Cloud Grid Comput., May 2011, pp. 434-443.
5. J. Yang, T. Yu, L. R. Jian, J. Qiu, and Y. Li, "An extreme automation framework for scaling cloud applications", IBM J. Res. Develop., vol. 55, no. 6, pp. 8:1-8:12, Nov. 2011.
6. E. Caron, F. Desprez, and A. Muresan, "Forecasting for grid and cloud computing on-demand resources based on pattern matching", in Proc. 2nd IEEE Int. Conf. Cloud Comput. Technol. Sci., Dec. 2010, pp. 456-463.
7. M. Sladescu, A. Fekete, K. Lee, and A. Liu, "Event aware workload prediction: A study using auction events", in Proc. 13th Int. Conf. Web Inf. Syst. Eng., ser. Lecture Notes Comput. Sci., 2012, vol. 7651, pp. 368-381.
8. S. Islam, J. Keung, K. Lee, and A. Liu, "Empirical prediction models for adaptive resource provisioning in the cloud", Future Generation Comput. Syst., vol. 28, no. 1, pp. 155-162, Jan. 2012.
9. R. N. Calheiros, R. Ranjan, and R. Buyya, "Virtual machine provisioning based on analytical performance and QoS in cloud computing environments", in Proc. 40th Int. Conf. Parallel Process., Sep. 2011, pp. 295-304.
10. G. E. P. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting and Control, 4th ed. Hoboken, NJ, USA: Wiley, 2008.
11. H. Zhang, G. Jiang, K. Kenji Yoshihira, H. Chen, and A. Saxena, "Intelligent workload factoring for a hybrid cloud computing model", in Proc. IEEE Congress Serv., Jul. 2009, pp. 701-708.
12. Z. Gong, X. Gu, and J. Wilkes, "PRESS: PRedictive Elastic ReSource Scaling for cloud systems", in Proc. 6th Int. Conf. Netw. Serv. Manage., Oct. 2010, pp. 9-16.
13. N. Roy, A. Dubey, and A. Gokhale, "Efficient autoscaling in the cloud using predictive models for workload forecasting", in Proc. 4th Int. Conf. Cloud Comput., Jul. 2011, pp. 500-507.
14. V. G. Tran, V. Debusschere, and S. Bacha, "Hourly server workload forecasting up to 168 hours ahead using seasonal ARIMA model", in Proc. 13th Int. Conf. Ind. Technol., Mar. 2012, pp. 1127-1131.
15. V. Nae, A. Iosup, and R. Prodan, "Dynamic resource provisioning in massively multiplayer online games", IEEE Trans. Parallel Distrib. Syst., vol. 22, no. 3, pp. 380-395, Mar. 2011.
16. S. Pacheco-Sanchez, G. Casale, B. Scotney, S. McClean, G. Parr, and S. Dawson, "Markovian workload characterization for QoS prediction in the cloud", in Proc. 4th Int. Conf. Cloud Comput., Jul. 2011, pp. 147-154.
17. G. Urdaneta, G. Pierre, and M. Van Steen, "Wikipedia workload analysis for decentralized hosting", Comput. Netw., vol. 53, no. 11, pp. 1830-1845, Jul. 2009.
18. M. Arlitt, and T. Jin, "A workload characterization study of the 1998 World Cup Web site", IEEE Netw., vol. 14, no. 3, pp. 30-37, May 2000.
19. M. Mao, J. Li, and M. Humphrey, "Cloud auto-scaling with deadline and budget constraints", in Proc. 11th Int. Conf. Grid Comput., Oct. 2010, pp. 41-48.
20. R. J. Hyndman, and Y. Khandakar, "Automatic time series forecasting: The forecast package for R", J. Statist. Softw., vol. 27, no. 3, pp. 1-22, Jul. 2008.
21. R. J. Hyndman, and G. Athanasopoulos. (2012). Forecasting: Principles and Practice, OTexts [Online]. Available: https://www.otexts.org/fpp
22. D. Kwiatkowski, P. C. Phillips, P. Schmidt, and Y. Shin, "Testing the null hypothesis of stationarity against the alternative of a unit root", J. Econometrics, vol. 54, no. 1-3, pp. 159-178, Oct. 1992.
23. F. Sowell, "Maximum likelihood estimation of stationary univariate fractionally integrated time series models", J. Econometrics, vol. 53, no. 1-3, pp. 165-188, Jul. 1992.
24. R. N. Calheiros, R. Ranjan, A. Beloglazov, C. A. FD Rose, and R. Buyya, "CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms", Softw.: Practice Exp., vol. 41, no. 1, pp. 23-50, Jan. 2011.