Models to evaluate service Provisioning over Cloud Computing Environments - A Blockchain-As-A-Service case study


  • Carlos Melo Federal University of Pernambuco
  • Jamilson Dantas Federal University of Pernambuco
  • Ronierison Maciel Federal University of Pernambuco
  • Paulo Silva Federal University of Pernambuco
  • Paulo Maciel Federal University of Pernambuco



Availability, Blockchain-as-a-Service, Hyper-converged, Virtualization


ThestrictnessoftheServiceLevelAgreements(SLAs)ismainlyduetoasetofconstraintsrelated to performance and dependability attributes, such as availability. This paper shows that system’s availability values may be improved by deploying services over a private environment, which may obtain better availability values with improved management, security, and control. However, how much a company needs to afford to keep this improved availability? As an additional activity, this paper compares the obtained availability values with the infrastructure deployment expenses and establishes a cost × benefit relationship. As for the system’s evaluation technique, we choose modeling; while for the service used to demonstrate the models’ feasibility, the blockchain-as-a-service was the selected one. This paper proposes and evaluate four different infrastructures hosting blockchains: (i) baseline; (ii) double redundant; (iii) triple redundant, and (iv) hyper-converged. The obtained results pointed out that the hyper-converged architecture had an advantage over a full triple redundant environment regarding availability and deployment cost.


Download data is not yet available.


HAAG, M. Hyper-Converged Infrastructures for DUM- MIES. [S.l.]: John Wiley & Sons, Inc., 2016.

MATOS, R. et al. Redundant eucalyptus private clouds: Availability modeling and sensitivity analysis. Journal of Grid Computing, v. 15, n. 1, p. 1–22, Mar 2017. Dispon ́ıvel em: ⟨⟩.

GUPTA, M. Blockchain for DUMMIES. [S.l.]: John Wi- ley & Sons, Inc., 2017.

ZYSKIND, G.; NATHAN, O.; PENTLAND, A. . Decen- tralizing privacy: Using blockchain to protect personal data. In: 2015 IEEE Security and Privacy Workshops. [S.l.: s.n.], 2015. p. 180–184.

CHRISTIDIS, K.; DEVETSIKIOTIS, M. Blockchains and smart contracts for the internet of things. IEEE Access, v. 4, p. 2292–2303, 2016.

KOSBA, A. et al. Hawk: The blockchain model of cryp- tography and privacy-preserving smart contracts. In: 2016 IEEE Symposium on Security and Privacy (SP). [S.l.: s.n.], 2016. p. 839–858.

WEBER, I. et al. On availability for blockchain-based systems. In: 2017 IEEE 36th Symposium on Reliable Dis- tributed Systems (SRDS). [S.l.: s.n.], 2017. p. 64–73.

XIAO, J. et al. Blockchain architecture reliability-based measurement for circuit unit importance. IEEE Access, v. 6, p. 15326–15334, 2018.

COSTA, I. et al. Availability evaluation and sensitivity analysis of a mobile backend-as-a-service platform. Journal Quality and Reliability Engineering International, 2015.

AZAGURY, A. C. et al. Gpfs-based implementation of a hyperconverged system for software defined infrastructure. IBM Journal of Research and Development, v. 58, n. 2/3, p. 6:1–6:12, March 2014.

U, A. et al. The efficient use of storage resources in san for storage tiering and caching. In: 2016 2nd Interna- tional Conference on Computational Intelligence and Net- works (CINE). [S.l.: s.n.], 2016. p. 118–122.

TANIGUCHI, Y. et al. Tandem equipment arranged ar- chitecture with exhaust heat reuse system for software-defined data center infrastructure. IEEE Transactions on Cloud Com- puting, v. 5, n. 2, p. 182–192, April 2017.

ZHANG, Y. et al. Vdc embedding scheme based on vir- tual nodes combination in software defined data center. In: 2016 IEEE Advanced Information Management, Communi- cates, Electronic and Automation Control Conference (IM- CEC). [S.l.: s.n.], 2016. p. 931–935.

MACIEL, P. et al. Dependability modeling. In: Perfor- mance and Dependability in Service Computing: Concepts, Techniques and Research Directions. [S.l.: s.n.], 2011.


AVIZIENIS, A. et al. Fundamental Concepts of Depend-

ability. University of Newcastle upon Tyne, Computing Sci- ence, 2001. (Technical report series). Dispon ́ıvel em: ⟨https: //⟩.

MALHOTRA, M.; TRIVEDI, K. Power-hierarchy of dependability-model types. Reliability, IEEE Transactions on, v. 43, n. 3, p. 493–502, Sep 1994.

SOFTWARE, I. Reliability Block Diagram. 2007. Http:// [Online; ac- cessed 26-September-2015].

GARG, S. et al. Analysis of software rejuvenation using markov regenerative stochastic petri net. In: Proc. In: Sixth International Symposium on Software Reliability Engineering, (ISSRE’95). Paderborn: [s.n.], 1995. p. 180–187.

DISTEFANO, S.; XING, L. A new approach to modeling the system reliability: dynamic reliability block diagrams. In: RAMS ’06. Annual Reliability and Maintainability Symposium, 2006. [S.l.: s.n.], 2006. p. 189–195.

XU, H.; XING, L.; ROBIDOUX, R. Drbd: Dynamic reliability block diagrams for system reliability modelling. In- ternational Journal of Computers and Applications, v. 31, n. 2, p. 132–141, 2009. Dispon ́ıvel em: ⟨http://www.tandfonline. com/doi/abs/10.1080/1206212X.2009.11441934⟩.

DANTAS, J. et al. Models for dependability analysis of cloud computing architectures for eucalyptus platform. International Transactions on Systems Science and Applications, v. 8, p. 13–25, 2012.

CAMPOS, E. et al. Stochastic modeling of auto scaling mechanism in private clouds for supporting performance tun- ning. In: Proceedings of the IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC’15). Hong Kong, China: [s.n.], 2015.




How to Cite

Melo, C., Dantas, J., Maciel, R., Silva, P., & Maciel, P. (2019). Models to evaluate service Provisioning over Cloud Computing Environments - A Blockchain-As-A-Service case study. Revista De Informática Teórica E Aplicada, 26(3), 65–74.



Regular Papers