Abstract
Cloud computing became widespread on IT industry, saving costs of acquisition and maintenance for companies of all sizes, and enabling fair management of resources according to the demand. Stochastic models can enable performance and dependability evaluation of cloud computing systems efficiently, what is needed for proper capacity planning. Distinct models may be combined in a hierarchy to address the huge number of components and levels of interaction among the system parts. Identification of bottlenecks in such composite models might be hard yet, due to the huge amount of input factors and variables which may interfere with the results. This paper proposes a method for bottleneck detection of computational systems represented with hierarchical models, that is remarkably applied in cloud computing systems. This is achieved through the composition of indices computed from lower level models in equations and solution methods of the top level model, for computing the sensitivity indices of all parameters with respect to a global system measure. A unified sensitivity ranking, comprising the composite indices, indicates the parameters with highest impact on output metrics. A case study supports the demonstration of accuracy and utility of our methodology. The study addresses a web service running on a private cloud with auto scaling mechanisms. The methods and algorithms presented here are helpful for decision-making when designing and managing cloud computing infrastructures, regarding incremental and architectural improvements.
Similar content being viewed by others
References
Avizienis, A., Laprie, J.C., Randell, B., Landwehr, C.E.: Basic concepts and taxonomy of dependable and secure computing. IEEE Trans. Depend. Sec. Comput. 1(1), 11–33 (2004)
Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the art of virtualization. SIGOPS Oper. Syst. Rev. 37, 164–177 (2003)
Blake, J.T., Reibman, A.L., Trivedi, K.S.: Sensitivity analysis of reliability and performability measures for multiprocessor systems. In: Proceedings of the 1988 ACM SIGMETRICS conference on Measurement and modeling of computer systems, pp. 177–186. ACM, New York, NY, USA (1988). http://doi.acm.org/10.1145/55595.55616
Bolch, G., Greiner, S., de Meer, H., Trivedi, K.S.: Queuing Networks and Markov Chains: modeling and performance evaluation with computer science applications, 2nd edn. Wiley, New York (2001)
Callou, G., Maciel, P., Tutsch, D., Ferreira, Ja, Araújo, J., Souza, R.: Estimating sustainability impact of high dependable data centers: A comparative study between brazilian and us energy mixes. Computing 95(12), 1137–1170 (2013)
Campos, E., Matos, R., Maciel, P., Costa, I., Silva, F.A., Souza, F.: Performance evaluation of virtual machines instantiation in a private cloud. In: Proceedings of the 2015 IEEE World Congress on Services. SERVICES 2015, pp. 319–326. IEEE Computer Society (2015)
Chuob, S., Pokharel, M., Park, J.S.: Modeling and analysis of cloud computing availability based on eucalyptus platform for e-government data center. In: 2011 Fifth international conference on innovative mobile and internet services in ubiquitous computing (IMIS), pp. 289–296 (2011). https://doi.org/10.1109/IMIS.2011.135
Cloth, L., Katoen, J.P., Khattri, M., Pulungan, R.: Model checking markov reward models with impulse rewards. In: Proceedings of the 2005 International Conference on Dependable Systems and Networks, DSN ’05, pp. 722–731. IEEE Computer Society, Washington, DC, USA (2005). https://doi.org/10.1109/DSN.2005.64
Dantas, J., Matos, R., Araujo, J., Maciel, P.: An availability model for eucalyptus platform: An analysis of warm-standy replication mechanism. In: Proceedings of the 2012 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2012). Seoul, Korea (2012)
Dantas, J., Matos, R., Araujo, J., Maciel, P.: Models for dependability analysis of cloud computing architectures for eucalyptus platform. Int. Trans. Syst. Sci. Appl. 8, 13–25 (2012)
Dantas, J., Matos, R., Araujo, J., Maciel, P.: Eucalyptus-based private clouds: availability modeling and comparison to the cost of a public cloud. Computing, pp. 1–20 (2015)
Eucalyptus: Official documentation for eucalyptus cloud (2014). Available on https://www.eucalyptus.com/docs/eucalyptus/4.0/
German, R.: Performance analysis of communication systems with non-markovian stochastic petri nets. Wiley, New York (2000)
German, R., Mitzlaff, J.: Transient analysis of deterministic and stochastic petri nets with timenet. In: Lecture Notes in Computer Science Vol. 977: Quantitative Evaluation of Computing and Communication Systems, pp. 209–223 (1995)
Ghosh, R., Longo, F., Naik, V.K., Trivedi, K.S.: Modeling and performance analysis of large scale IaaS clouds. Future Gener. Comput. Syst. 29(5), 1216–1234 (2013)
Gokhale, S.S., Trivedi, K.S.: Reliability prediction and sensitivity analysis based on software architecture. In: 13th International Symposium on Software Reliability Engineering, 2002. Proceedings., pp. 64–75. IEEE (2002)
Goyal, D., Kumar, A., Saini, M., Joshi, H.: Reliability, maintainability and sensitivity analysis of physical processing unit of sewage treatment plant. SN Appl. Sci. 1(11), 1507 (2019)
Jain, R.: The art of computer systems performance analysis: techniques for experimental design, measurement, simulation and modeling. Wiley-Interscience, New York (1991)
Kleinrock, L.: Queueing systems, vol. 1. Wiley, New York (1975)
Kolmogorov, A.: Über die analytischen methoden in der wahrscheinlichkeitsrechnung. Springer-Verlag, Mathematische Annalen. Newyork (1931). (in german)
Kuo, W., Zuo, M.: Optimal reliability modeling: principles and applications. Wiley, New York (2003)
Liu, B., Chang, X., Han, Z., Trivedi, K., Rodríguez, R.J.: Model-based sensitivity analysis of iaas cloud availability. Future Generation Computer Systems 83, 1–13 (2018). https://doi.org/10.1016/j.future.2017.12.062. http://www.sciencedirect.com/science/article/pii/S0167739X17301796
Longo, F., Ghosh, R., Naik, V., Trivedi, K.: A scalable availability model for infrastructure-as-a-service cloud. In: Proceedings of the 2011 IEEE/IFIP 41st International Conference on Dependable Systems Networks (DSN), pp. 335 –346 (2011)
Maciel, P., Trivedi, K.S., Matias, R., Kim, D.S.: Dependability modeling. In: Performance and Dependability in Service Computing: Concepts, Techniques and Research Directions. IGI Global, Hershey (2011)
Malhotra, M., Trivedi, K.S.: Power-hierarchy of dependability-model types. IEEE Trans. Reliab. 43(3), 493–502 (1994)
Marsan, M.A., Conte, G., Balbo, G.: A class of generalized stochastic petri nets for the performance evaluation of multiprocessor systems. ACM Trans. Comput. Syst. 2, 93–122 (1984)
Matos, R.: Identification of availability and performance bottlenecks in cloud computing systems: An approach based on hierarchical models and sensitivity analysis. Ph.D. thesis, Universidade Federal de Pernambuco – UFPE, Recife, Brazil (2016)
Matos, R., Araujo, J., Oliveira, D., Maciel, P., Trivedi, K.: Sensitivity analysis of a hierarchical model of mobile cloud computing. Simul. Model. Pract. Theory 50, 151–164 (2014)
Matos, R., Dantas, J., Araujo, J., Trivedi, K.S., Maciel, P.: Redundant eucalyptus private clouds: availability modeling and sensitivity analysis. J. Grid Comput. 15(1), 1–22 (2017)
Matos, R.D.S., Maciel, P.R.M., Machida, F., Kim, D.S., Trivedi, K.S.: Sensitivity analysis of server virtualized system availability. IEEE Trans. Reliabil. 61(4), 994–1006 (2012). https://doi.org/10.1109/TR.2012.2220711
Matos, R.S., Maciel, P.R., Silva, R.M.: Qos-driven optimisation of composite web services: an approach based on grasp and analytical models. Int. J. Web Grid Serv. 9(3), 304–321 (2013)
Matos Júnior, R.d.S.: An automated approach for systems performance and dependability improvement through sensitivity analysis of markov chains. Master’s thesis, Universidade Federal de Pernambuco – UFPE, Recife, Brazil (2011)
Melo, R., Bezerra, M., Dantas, J., Matos, R., de Melo Filho, I., Oliveira, A., Feliciano, F., Maciel, P.: Sensitivity analysis techniques applied in video streaming service on eucalyptus cloud environments. J. Inform. Syst. Eng. Manag. 3(1), 02 (2018)
Menascé, D.A., Almeida, V.A., Dowdy, L.W.: Performance by design: computer capacity planning by example. Prentice Hall PTR, London (2004)
Mills, K., Filliben, J., Dabrowski, C.: An efficient sensitivity analysis method for large cloud simulations. In: 2011 IEEE 4th International Conference on Cloud Computing, pp. 724–731 (2011)
Molloy, M.K.: Performance analysis using stochastic petri nets. IEEE Trans. Comput. 31(9), 913–917 (1982). https://doi.org/10.1109/TC.1982.1676110
Muppala, J.K., Trivedi, K.S.: GSPN models: sensitivity analysis and applications. In: ACM-SE 28: Proceedings of the 28th annual Southeast regional conference, pp. 25–33. ACM, New York, NY, USA (1990). https://doi.org/10.1145/98949.98962
Murata, T.: Petri nets: properties, analysis and applications. Proc. IEEE 77(4), 541–580 (1989)
Nguyen, T.A., Min, D., Choi, E., Tran, T.D.: Reliability and availability evaluation for cloud data center networks using hierarchical models. IEEE Access 7, 9273–9313 (2019). https://doi.org/10.1109/ACCESS.2019.2891282
O’Connor, P.P., Kleyner, A.: Practical reliability engineering, 5th edn. Wiley Publishing, New York (2012)
Qin, J., Li, Z.: Reliability and sensitivity analysis method for a multistate system with common cause failure. Complexity 2019 (2019)
Silva, B., Matos, R., Callou, G., Figueiredo, J., Oliveira, D., Ferreir, J., Dantas, J., Lobo Junior, A., Alves, V., Maciel, P.: Mercury: An integrated environment for performance and dependability evaluation of general systems. In: Proceedings of Industrial Track at 45th Dependable Systems and Networks Conference, DSN 2015. IEEE, Rio de Janeiro (2015)
Trivedi, K.S.: Probability and statistics with reliability, queuing, and computer science applications, 2nd edn. Wiley, New York (2001)
Voorsluys, W., Broberg, J., Venugopal, S., Buyya, R.: Cost of virtual machine live migration in clouds. Lecture Notes in Computer Science, New York, Springer-Verlag (2009)
Watson, J.F.I., Desrochers, A.: Applying generalized stochastic petri nets to manufacturing systems containing nonexponential transition functions. Syst. Man Cybern. IEEE Trans. 21(5), 1008–1017 (1991)
Wei, B., Lin, C., Kong, X.: Dependability modeling and analysis for the virtual data center of cloud computing. In: Proceedings of the 2011 IEEE International Conference on High Performance Computing and Communications, HPCC ’11, pp. 784–789. IEEE Computer Society, Washington, DC, USA (2011)
Acknowledgements
This study is funded by Army Research Office (Grant No. W911NF1810413).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Matos, R., Dantas, J., Araujo, E. et al. Bottleneck Detection in Cloud Computing Performance and Dependability: Sensitivity Rankings for Hierarchical Models. J Netw Syst Manage 28, 1839–1871 (2020). https://doi.org/10.1007/s10922-020-09562-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10922-020-09562-9