Skip to main content

Multi-cloud Solution Design for Migrating a Portfolio of Applications to the Cloud

  • 989 Accesses

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 12632)

Abstract

Migrating applications to the cloud is rapidly increasing in many organizations as it enables them to take advantages of the cloud, such as the lower costs and accessibility of data. Moreover, such organizations typically try to avoid sticking to a single cloud provider and rather prefer to be able to spread out their applications across different providers. However, there are many challenges in achieving this. First, many of the applications that are required to be moved to the cloud might be legacy applications that do not have good documentation, and so it is not trivial to even assess whether it is feasible to move them to the cloud or not. Moreover, such legacy applications might need a significant architecture overhaul to achieve the task of moving them to the cloud. Large client may have significant percentage of applications in this category. So, one has to evaluate cloud feasibility and understand whether there is a need to re-architect application based on what services providers are able to offer. Second, clients usually define multiple features, encryption/security level, and other service level requirements they expect in the providers they will migrate each of their applications to. Thus, choosing the right providers for different application is another challenging task here. In this work-in-progress paper, we present a novel methodology for preparing such a cloud migration solution, where we perform text mining on application data to evaluate cloud-migration feasibility and then recommend the optimal solution using a mathematical optimization model. We illustrate our approach with an example use case.

Keywords

  • Cloud computing
  • Multi-cloud
  • Cloud feasibility
  • Text mining
  • Cloud migration
  • Optimization

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-030-76352-7_44
  • Chapter length: 10 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   84.99
Price excludes VAT (USA)
  • ISBN: 978-3-030-76352-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   109.99
Price excludes VAT (USA)
Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.

References

  1. Mohamed, M., Megahed, A.: Optimal assignment of autonomic managers to cloud resources. In: 2015 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), pp. 88–93. IEEE (2015)

    Google Scholar 

  2. Megahed, A., Mohamed, M., Tata, S.: A stochastic optimization approach for cloud elasticity. In: 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), pp. 456–463 (2017)

    Google Scholar 

  3. IBM blog-‘New IBM services help companies manage the new multicloud world’

    Google Scholar 

  4. Litchfield, A., Althouse, J.: A systematic review of cloud computing, big data and databases on the cloud. In: Americas’ Conference on Information Systems (AMCIS) (2014)

    Google Scholar 

  5. Newlin Rajkumar, V.: Security measures in cloud computing an extensive assessment. Int. J. Adv. Inf. Commun. Technol. 4, 405–410 (2014)

    Google Scholar 

  6. Cranford, N.: Five challenges of cloud migration. RCR Wirel News (2017). https://www.rcrwireless.com/20171003/five-challenges-of-cloud-migration-tag27-tag99

  7. Pamami, P., Jain, A., Sharma, N.: Cloud migration metamodel: a framework for legacy to cloud migration. In: 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), pp. 43–50 (2019)

    Google Scholar 

  8. Iqbal, A., Colomo-Palacios, R.: Key opportunities and challenges of data migration in cloud: results from a multivocal literature review. Procedia Comput. Sci. 164, 48–55 (2019)

    CrossRef  Google Scholar 

  9. Ilyas, I., Modh, M.M.: Implementing comparison of cloud service provider package offerings. U.S. Patent 9,818,127, issued 14 November 2017 (2017)

    Google Scholar 

  10. Iyoob, I., Yan, A.M.: Assessment of best fit cloud deployment infrastructures. U.S. Patent 9,813,318, issued 7 November 2017 (2017)

    Google Scholar 

  11. Iyoob, I., Modh, M., Farooq, M.S.: Assessment of best fit cloud deployment infrastructures. U.S. Patent Application 14/140,443, filed 18 September 2014 (2014)

    Google Scholar 

  12. Yang, J.: Hybrid cloud computing solution for streamlined genome data analysis. In: 9th International Conference on Management of Digital EcoSystems, pp. 173–180 (2017)

    Google Scholar 

  13. Megahed, A., et al.: An optimization-based approach for cloud solution design. In: Panetto, H., et al. (eds.) OTM 2017. LNCS, vol. 10573, pp. 751–764. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69462-7_47

    CrossRef  Google Scholar 

  14. Megahed, A., Nazeem, A., Yin, P., Tata, S., Nezhad, H.R.M., Nakamura, T.: Optimizing cloud solutioning design. Future Gener. Comput. Syst. 91, 407–424 (2019)

    Google Scholar 

  15. Singh, G., Malhotra, M., Sharma, A.: An agent based virtual machine migration process for cloud environment. In: 2019 4th International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU), pp. 1–4 (2019)

    Google Scholar 

  16. Guillén, J., Miranda, J., Murillo, J.M., Canal, C.: Developing migratable multicloud applications based on MDE and adaptation techniques. In: Second Nordic Symposium on Cloud Computing & Internet Technologies, pp. 30–37 (2013)

    Google Scholar 

  17. Jamshidi, P., Pahl, C., Mendonça, N.C.: Pattern‐based multi‐cloud architecture migration. Softw.: Pract. Exp. 47(9), 1159–1184 (2017)

    Google Scholar 

  18. Wang, K.: Migration strategy of cloud collaborative computing for delay-sensitive industrial IoT applications in the context of intelligent manufacturing. Comput. Commun. 150, 413–420 (2020)

    CrossRef  Google Scholar 

  19. Stauffer, J.M., Megahed, A., Sriskandarajah, C.: Elasticity management for capacity planning in software as a service cloud computing. IISE Trans. 53(4), 1–69 (2020)

    Google Scholar 

  20. Megahed, A., Mohamed, M., Tata, S.: Cognitive elasticity of cloud applications. U.S. Patent Application 15/814,608. International Business Machines Corp, (2019)

    Google Scholar 

  21. Coutinho, E.F., Neto, M.M., Moreira, L.O., de Souza, J.N.: Analysis of elasticity impact in hybrid computational clouds. In: Euro American Conference on Telematics and Information Systems, pp. 1–8 (2018)

    Google Scholar 

  22. Tyagi, N., Rana, A., Kansal, V.: Creating elasticity with enhanced weighted optimization load balancing algorithm in cloud computing. In: 2019 Amity International Conference on Artificial Intelligence (AICAI), pp. 600–604 (2019)

    Google Scholar 

  23. Teyeb, H., Hadj-Alouane, N.B., Tata, S., Balma, A.: Optimal dynamic placement of virtual machines in geographically distributed cloud data centers. Int. J. Coop. Inf. Syst. 26(3), 1750001 (2017)

    CrossRef  Google Scholar 

  24. Routray, R., Megahed, A., Tata, S.: Cognitive classification of workload behaviors in multi-tenant cloud computing environments. U.S. Patent Application 16/051,192. International Business Machines Corp (2020)

    Google Scholar 

  25. Megahed, A., Mohamed, M., Tata, S.: Cognitive allocation of monitoring resources for cloud applications. U.S. Patent Application 16/147,136. International Business Machines Corp (2020)

    Google Scholar 

  26. Megahed, A., Routray, R., Tata, S.: Cognitive handling of workload requests. U.S. Patent Application 16/129,042. International Business Machines Corp (2020)

    Google Scholar 

  27. Amato, A., Venticinque, S.: Multiobjective optimization for brokering of multicloud service composition. ACM Trans. Internet Technol. (TOIT) 16(2), 1–20 (2016)

    CrossRef  Google Scholar 

  28. Iyoob, I., Zarifoglu, E., Dieker, A.B.: Cloud computing operations research. Serv. Sci. 5(2), 88–101 (2013)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shubhi Asthana .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Asthana, S., Megahed, A., Iyoob, I. (2021). Multi-cloud Solution Design for Migrating a Portfolio of Applications to the Cloud. In: , et al. Service-Oriented Computing – ICSOC 2020 Workshops. ICSOC 2020. Lecture Notes in Computer Science(), vol 12632. Springer, Cham. https://doi.org/10.1007/978-3-030-76352-7_44

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-76352-7_44

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76351-0

  • Online ISBN: 978-3-030-76352-7

  • eBook Packages: Computer ScienceComputer Science (R0)