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Distributed application provisioning over Ethereum-based private and permissioned blockchain: availability modeling, capacity, and costs planning

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Abstract

Blockchain and cloud computing are two of the main topics related to the distributed computing paradigm, and in the last decade, they have seen exponential growth in their adoption. Cloud computing has long been established as the main mechanism to test, develop, and deliver new applications and services in a distributed manner across the World Wide Web. Large data centers host many services and store petabytes of user data. Infrastructure and services owners rule the access to data and may even be able to change contents and attest to its veracity. Blockchain is a step towards a future where the user’s data are considered safer, besides being public. Advances in blockchain-based technologies, now, support service provisioning over permissioned and private infrastructures. Therefore, organizations or groups of individuals may share information, service even if they do not trust each other, besides supporting infrastructure management tasks. This paper presents and evaluates models for assessing the availability and capacity-oriented availability of cloud computing infrastructures. It aims at running blockchain’s distributed applications based on the Ethereum blockchain platform and the required expenses to perform service delivery in public and private infrastructures. Most of the obtained results also apply to other blockchains-based platforms.

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Notes

  1. Ethereum: https://hub.docker.com/u/ethereum.

  2. https://paonline56.itcs.hpe.com/?Page=Index.

References

  1. Amazon (2020) What is cloud computing? https://aws.amazon.com/pt/what-is-cloud-computing/. Accessed 2 Apr 2020

  2. Aniello L, Baldoni R, Gaetani E, Lombardi F, Margheri A, Sassone V (2017) A prototype evaluation of a tamper-resistant high performance blockchain-based transaction log for a distributed database. In: 2017 13th European Dependable Computing Conference (EDCC). IEEE, pp 151–154

  3. Arundel J, Domingus J (2019) Cloud Native DevOps with Kubernetes: building, deploying, and scaling modern applications in the Cloud. O’Reilly Media, Newton

    Google Scholar 

  4. Avizienis A, Laprie J, Randell B, Landwehr C (2004) Basic concepts and taxonomy of dependable and secure computing. IEEE Trans Depend Secure Comput 1:11–33

    Article  Google Scholar 

  5. Avižienis A, Laprie J, Randell B (2001) Fundamental concepts of dependability. Technical report series. University of Newcastle upon Tyne, Computing Science. https://books.google.com.br/books?id=cDkmGwAACAAJ

  6. Buterin V et al (2013) Ethereum white paper. GitHub repository, vol 1, pp 22–23

  7. Dantas J (2013) Modelos para analise de dependabilidade de arquiteturas de computao em nuvem. Master’s thesis, Centro de Informtica—Universidade Federal de Pernambuco (Recife, Brasil)

  8. Dantas J, Matos R, Melo C, Maciel P (2020) Cloud infrastructure planning: models considering an optimization method, cost and performance requirements. Int J Grid Utility Computing. https://www.inderscience.com/jhome.php?jcode=ijguc

  9. Frank PM (1978) Introduction to sensitivity analysis. Academic Press, London

    Google Scholar 

  10. Garg S, Puliafito A, Telek M, Trivedi KS (1995) Analysis of software rejuvenation using Markov regenerative stochastic Petri net. In: Proceedings of Sixth International Symposium on Software Reliability Engineering, (ISSRE’95). Paderborn, pp 180–187

  11. Gupta M (2017) Blockchain for DUMMIES. Wiley, New York

    Google Scholar 

  12. Hightower K, Burns B, Beda J (2017) Kubernetes: up and running—dive into the future of infrastructure. O’Reilly Media, Inc., Newton

    Google Scholar 

  13. Jain R (1991) The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. Wiley Computer Publishing, Wiley, New York

    MATH  Google Scholar 

  14. Li QL, Ma JY, Chang YX (2018) Blockchain queueing theory. arXiv preprint arXiv:1808.01795

  15. Maciel P, Matos R, Silva B, Figueiredo J, Oliveira D, Fé I, Maciel R, Dantas J (2017) Mercury: performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In: 2017 IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC), pp 50–57. https://doi.org/10.1109/PRDC.2017.16

  16. Maciel PR, Trivedi KS, Matias R, Kim DS (2012) Dependability Modeling. In: Cardellini V, Casalicchio E, Castelo Branco KL, Estrella JC, Monaco FJ (eds) Performance and Dependability in Service Computing: Concepts, Techniques and Research Directions. IGI Global, pp 53–97

  17. Malhotra M, Trivedi K (1994) Power-hierarchy of dependability-model types. IEEE Trans Reliab 43(3):493–502. https://doi.org/10.1109/24.326452

    Article  Google Scholar 

  18. Maciel PRM (2016) Modeling availability impact in cloud computing. Springer International Publishing, Cham, pp 287–320

    Google Scholar 

  19. Matos R, Araujo J, Oliveira D, Maciel P, Trivedi K (2015) Sensitivity analysis of a hierarchical model of mobile cloud computing. Simul Modell Pract Theory 50:151–164. https://doi.org/10.1016/j.simpat.2014.04.003 Special Issue on Resource Management in Mobile Clouds

    Article  Google Scholar 

  20. Matos R, Dantas J, Araujo J, Trivedi KS, Maciel P (2017) Redundant eucalyptus private clouds: availability modeling and sensitivity analysis. J Grid Comput 15(1):1–22

    Article  Google Scholar 

  21. Mell MP, Grance T (2011) SP 800–145. The NIST Definition of Cloud Computing. National Institute of Standards & Technology, Gaithersburg, MD, USA.

  22. Melo C, Dantas J, Araujo J, Maciel P (2016) Availability models for synchronization server infrastructure. In: Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC’16). Budapest

  23. 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

    Article  Google Scholar 

  24. Melo C, Dantas J, Oliveira D, Fé I, Matos R, Dantas R, Maciel R, Maciel P (2018) Dependability evaluation of a blockchain-as-a-service environment. In: 2018 IEEE Symposium on Computers and Communications (ISCC). IEEE, pp 00909–00914

  25. Melo C, Matos R, Dantas J, Maciel P (2017) Capacity-oriented availability model for resources estimation on private cloud infrastructure. In: 2017 IEEE 22nd Pacific Rim International Symposium on Dependable Computing (PRDC). IEEE, pp 255–260

  26. Molloy MK (1981) On the integration of delay and throughput measures in distributed processing models. Ph.D. thesis, University of California, Los Angeles

  27. Murata T (1989) Petri nets: properties, analysis and applications. Proc IEEE 77(4):541–580. https://doi.org/10.1109/5.24143

    Article  Google Scholar 

  28. Nakamoto S (2019) Bitcoin: A peer-to-peer electronic cash system. TechnicalReport, Manubot

    Google Scholar 

  29. Öhmann D, Simsek M, Fettweis GP (2014) Achieving high availability in wireless networks by an optimal number of Rayleigh-fading links. In: 2014 IEEE Globecom Workshops (GC Wkshps). IEEE, pp 1402–1407

  30. Onik MMH, Miraz MH (2019) Performance analytical comparison of blockchain-as-a-Service (BaaS) platforms. In: International Conference for Emerging Technologies in Computing. Springer, Berlin, pp 3–18

  31. Pongnumkul S, Siripanpornchana C, Thajchayapong S (2017) Performance analysis of private blockchain platforms in varying workloads. In: 2017 26th International Conference on Computer Communication and Networks (ICCCN). Vancouver, BC, 2017, pp 1–6

  32. Roehrs A, da Costa CA, da Rosa Righi R, da Silva VF, Goldim JR, Schmidt DC (2019) Analyzing the performance of a blockchain-based personal health record implementation. J Biomed Inform 92:103140

    Article  Google Scholar 

  33. Sebastio S, Ghosh R, Mukherjee T (2018) An availability analysis approach for deployment configurations of containers. IEEE Trans Serv Comput. https://doi.org/10.1109/TSC.2017.2788442

    Article  Google Scholar 

  34. Sukhwani H, Martínez JM, Chang X, Trivedi KS, Rindos A (2017) Performance modeling of PBFT consensus process for permissioned blockchain network (hyperledger fabric). In: 2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS). IEEE, pp 253–255

  35. Sukhwani H, Wang N, Trivedi KS, Rindos A (2018) Performance modeling of hyperledger fabric (permissioned blockchain network). In: 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA). IEEE, pp 1–8

  36. Torquato M, Torquato L, Maciel P (2018) Models for capacity oriented availability evaluation of a private cloud. Revista de Informática Teórica e Aplicada-RITA-ISSN 2175:2745

    Google Scholar 

  37. Trivedi KS, Hunter S, Garg S, Fricks R (1996) Reliability analysis techniques explored through a communication network example. North Carolina State University, Center for Advanced Computing and Communication

    Google Scholar 

  38. Vaqueiro LM, Rodero-Merino L, Caceres J, Lindner M (2009) A break in the clouds: towards a cloud definition. Comput Commun Rev 39:50–55

    Article  Google Scholar 

  39. Weber I, Gramoli V, Ponomarev A, Staples M, Holz R, Tran AB, Rimba P (2017) On availability for blockchain-based systems. In: 2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS), pp 64–73. https://doi.org/10.1109/SRDS.2017.15

  40. Zhang H, Jin C, Cui H (2018) A method to predict the performance and storage of executing contract for ethereum consortium-blockchain. In: International Conference on Blockchain. Springer, Berlin, pp 63–74

  41. Zyskind G, Nathan O, Pentland A (2015) Decentralizing privacy: using blockchain to protect personal data. In: 2015 IEEE Security and Privacy Workshops, pp 180–184. https://doi.org/10.1109/SPW.2015.27

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Acknowledgements

The authors would like to thank the Brazilian Government for the financial support through the Fundação de Amparo a Ciência e Tecnologia de Pernambuco (FACEPE), the Modeling of Distributed and Concurrent Systems (MoDCS) group for the help on improving this research.

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Correspondence to Carlos Melo.

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Melo, C., Dantas, J., Pereira, P. et al. Distributed application provisioning over Ethereum-based private and permissioned blockchain: availability modeling, capacity, and costs planning. J Supercomput 77, 9615–9641 (2021). https://doi.org/10.1007/s11227-020-03617-z

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