Skip to main content
SpringerLink
Log in

Dependability evaluation of a disaster recovery solution for IoT infrastructures

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The ongoing miniaturization and cost reduction of electronic devices (microprocessors, sensors, batteries, and wireless communication units) have allowed the proliferation of the Internet of Things (IoT)-based applications. Many of these applications are mission-critical (e.g., healthcare and traffic road management), in the sense that the IoT system needs to take critical decisions in real-time. Hence, these IoT systems need to be designed using effective fault-tolerant techniques like disaster recovery (DR) solutions. This work proposes a Petri net-based approach for modeling and analysis of DR solutions for IoT infrastructures. The proposed models allow assessing important DR measures, such as system availability, cost, and recovery time objective. To demonstrate the feasibility of our approach, we present a case study in which a real-world healthcare IoT system is modeled and analyzed. Besides, sensitivity analysis is carried out to assess the effects of model parameters on the system availability.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Andrade E, Nogueira B, Matos R, Callou G, Maciel P (2017) Availability modeling and analysis of a disaster-recovery-as-a-service solution. Computing 99:1–26

    Article  MathSciNet  Google Scholar 

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

    Article  Google Scholar 

  3. Blake JT, Reibman AL, Trivedi KS (1988) 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. ACM, New York, NY, pp 177–186

  4. Bolch G, Greiner S, de Meer H, Trivedi KS (2001) Queuing networks and Markov chains: modeling and performance evaluation with computer science applications, 2nd edn. Wiley, Hoboken

    MATH  Google Scholar 

  5. Dantas J, Matos R, Araujo J, Maciel P (2012) An availability model for eucalyptus platform: an analysis of warm-standy replication mechanism. In: 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, pp 1664–1669

  6. Dantas J, Matos R, Araujo J, Maciel P (2015) Eucalyptus-based private clouds: availability modeling and comparison to the cost of a public cloud. Computing 97(11):1121–1140

    Article  MathSciNet  Google Scholar 

  7. Desai C (2009) TC74-product qualification report. Tech. rep., Microchip Technology Inc

  8. dos Santos RP, Almeida RMV (2010) Hospital medical equipment maintenance schedules using the mean time between failures. Rio J (RJ) Braz 18(2):309–314

    Google Scholar 

  9. Dwyer SJ III, Weaver AC, Hughes KK (2004) Health insurance portability and accountability act. Secur Issues Digit Med Enterp 72(2):9–18

    Google Scholar 

  10. Friedman T, Perkins E, Velosa A, Schulte WR, Steenstrup K (2015) Predicts 2016: unexpected implications arising from the internet of things. Tech. rep., Gartner Inc

  11. German R (2000) Performance analysis of communication systems with non-Markovian stochastic Petri nets. Wiley, New York

    MATH  Google Scholar 

  12. Goel S, Buyya R (2007) Data replication strategies in wide-area distributed systems. In: Enterprise service computing: from concept to deployment. IGI Global, pp 211–241

  13. Grimsmo SB (2009) Reliability issues when providing M2M services in the Internet of Things. Master’s thesis, Institutt for telematikk

  14. Gubbi J, Buyya R, Marusic S, Palaniswami M (2013) Internet of Things (IoT): a vision, architectural elements, and future directions. Future Gener Comput Syst 29(7):1645–1660

    Article  Google Scholar 

  15. Hoffman FO, Gardner RH (1983) Evaluation of uncertainties in environmental radiological assessment models. Radiological assessments: a textbook on environmental dose assessment, pp 11–1

  16. Hu P, Ning H, Qiu T, Song H, Wang Y, Yao X (2017) Security and privacy preservation scheme of face identification and resolution framework using fog computing in internet of things. IEEE Internet Things J

  17. Hu T, Guo M, Guo S, Ozaki H, Zheng L, Ota K, Dong M (2010) Mttf of composite web services. In: 2010 International Symposium on Parallel and Distributed Processing with Applications (ISPA). IEEE, pp 130–137

  18. Jain R (1990) The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. Wiley, Hoboken

    Google Scholar 

  19. Kharkongor C, Chithralekha T, Varghese R (2017) Trust and energy-efficient routing for internet of things energy evaluation model. In: Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications. Springer, Berlin, pp 585–597

  20. Kim DS, Machida F, Trivedi KS (2009) Availability modeling and analysis of a virtualized system. In: 15th IEEE Pacific Rim International Symposium on Dependable Computing, 2009, PRDC’09. IEEE, pp 365–371

  21. Macedo D, Guedes LA, Silva I (2014) A dependability evaluation for internet of things incorporating redundancy aspects. In: 2014 IEEE 11th International Conference on Networking, Sensing and Control (ICNSC). IEEE, pp 417–422

  22. Machida F, Andrade E, Kim D, Trivedi K (2011) Candy: component-based availability modeling framework for cloud service management using sysml. In: 2011 30th IEEE Symposium on Reliable Distributed Systems (SRDS). IEEE, pp 209–218

  23. Maciel P, Trivedi KS, Matias R, Kim DS (2011) Dependability modeling. In: Performance and dependability in service computing: concepts, techniques and research directions. IGI Global, Hershey

  24. Marsan MA, Conte G, Balbo G (1984) A class of generalized stochastic Petri nets for the performance evaluation of multiprocessor systems. ACM Trans Comput Syst 2:93–122

    Article  Google Scholar 

  25. 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 

  26. Medical D (2014) Gamma/Gamma XL patient monitors. Tech. rep., Drger Medical AG & Co

  27. Mkalaf K, Gibson P, Flanagan J (2013) A study of current maintenance strategies and the reliability of critical medical equipment in hospitals in relation to patient outcomes. Int J Manag Sci Eng

  28. Molloy MK (1982) Performance analysis using stochastic Petri nets. IEEE Trans Comput 31(9):913–917

    Article  Google Scholar 

  29. Morris S et al (1995) Reliability toolkit: commercial practices edition: a practical guide for commercial products and military systems under acquisition reform, Reliability Analysis Center, IIT Research Institute, Rome, NY

  30. Nguyen TA, Kim DS, Park JS (2016) Availability modeling and analysis of a data center for disaster tolerance. Future Gener Comput Syst 56:27–50

    Article  Google Scholar 

  31. O’Connor PP, Kleyner A (2012) Practical reliability engineering, 5th edn. Wiley, Hoboken

    Google Scholar 

  32. Oppermann FJ, Boano CA, Zuniga MA, Römer K (2015) Automatic protocol configuration for dependable internet of things applications. In: 2015 IEEE 40th Local Computer Networks Conference Workshops (LCN Workshops). IEEE, pp 742–750

  33. Perlin M (2013) Data center downtime cost averages $7,900 a minute. http://www.fiercehealthcare.com/it/data-center-downtime-cost-averages-7-900-a-minute

  34. Reese G (2009) Cloud application architectures. O’Reilly Media Inc, Sebastopol

    Google Scholar 

  35. Rehman Z, Hussain OK, Hussain FK (2012) Iaas cloud selection using MCDM methods. In: 2012 IEEE Ninth International Conference on E-Business Engineering (ICEBE), pp 246–251. https://doi.org/10.1109/ICEBE.2012.47

  36. Sánchez-Arias G, García CG, G-Bustelo BCP (2017) Midgar: study of communications security among smart objects using a platform of heterogeneous devices for the Internet of Things. Future Gener Comput Syst 74:444–466

    Article  Google Scholar 

  37. Sanislav T, Mois G, Miclea L (2016) An approach to model dependability of cyber-physical systems. Microprocess Microsyst 41:67–76

    Article  Google Scholar 

  38. Silva B, Maciel P, Tavares E, Zimmermann A (2013) Dependability models for designing disaster tolerant cloud computing systems. In: 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, pp 1–6

  39. Silva B, Maciel P, Zimmermann A (2013) Performability models for designing disaster tolerant infrastructure-as-a-service cloud computing systems. In: 2013 8th International Conference for Internet Technology and Secured Transactions (ICITST). IEEE, pp 647–652

  40. Silva B, Matos R, Callou G, Figueiredo J, Oliveira D, Ferreira J, Dantas J, Junior A, Alves V, Maciel P (2015) 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)

  41. Silva I, Leandro R, Macedo D, Guedes LA (2013) A dependability evaluation tool for the Internet of Things. Comput Electr Eng 39(7):2005–2018

    Article  Google Scholar 

  42. Stojkoska BLR, Trivodaliev KV (2017) A review of Internet of Things for smart home: challenges and solutions. J Clean Prod 140:1454–1464

    Article  Google Scholar 

  43. Trivedi KS (2001) Probability and statistics with reliability, queuing, and computer science applications, 2nd edn. Wiley, Hoboken

    MATH  Google Scholar 

  44. Wang J, Hu C, Liu A (2017) Comprehensive optimization of energy consumption and delay performance for green communication in Internet of Things. Mob Inf Syst 2017(2017):3206160

  45. Wood T, Cecchet E, Ramakrishnan K, Shenoy P, Van der Merwe J, Venkataramani A (2010) Disaster recovery as a cloud service: economic benefits and deployment challenges. In: Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing. USENIX Association, pp 8–8

  46. Yaqoob I, Ahmed E, Hashem IAT, Ahmed AIA, Gani A, Imran M, Guizani M (2017) Internet of things architecture: recent advances, taxonomy, requirements, and open challenges. IEEE Wirel Commun 24(3):10–16

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Statistics and Informatics Department (DEINFO), Federal Rural University of Pernambuco, Recife, PE, Brazil

    Ermeson Andrade

  2. Academic Unit of Garanhuns (UAG), Federal Rural University of Pernambuco, Garanhuns, PE, Brazil

    Bruno Nogueira

Authors
  1. Ermeson Andrade
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bruno Nogueira
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ermeson Andrade.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Andrade, E., Nogueira, B. Dependability evaluation of a disaster recovery solution for IoT infrastructures. J Supercomput 76, 1828–1849 (2020). https://doi.org/10.1007/s11227-018-2290-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-018-2290-0

Keywords

Search

Navigation