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Using Docker Swarm with a User-Centric Decision-Making Framework for Cloud Application Migration

  • Esha Barlaskar
  • Peter Kilpatrick
  • Ivor Spence
  • Dimitrios S. Nikolopoulos
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 864)

Abstract

Vendor lock-in is a major obstacle for cloud users in performing multi-cloud deployment or inter-cloud migration, due to the lack of standardization. Current research efforts tackling the inter-cloud migration problem are commonly technology-oriented with significant performance overheads. Moreover, current studies do not provide adequate support for decision making such as why and when inter-cloud migration should take place. We propose the architecture and the problem formulation of a Multi-objective dYnamic MIgratioN Decision makER (MyMinder) framework that assists cloud users in achieving a stable QoS performance in the post-deployment phase by helping decide on actions to be taken as well as providing support to achieve such actions. Additionally, we demonstrate the migration capability of MyMinder by proposing an Automated Triggering Algorithm (ATA), which uses existing Docker Swarm technology for application migration.

Keywords

Cloud Computing Dynamic decision making QoS monitoring Inter-cloud migration Docker Swarm 

References

  1. 1.
    Barlaskar, E., Kilpatrick, P., Spence, I., Nikolopoulos, D.S.: MyMinder: a user-centric decision making framework for intercloud migration. In: Proceedings of the 7th International Conference on Cloud Computing and Services Science, pp. 588–595 (2017)Google Scholar
  2. 2.
    Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., Ignatius, J.: Review: a state-of the-art survey of topsis applications. Expert Syst. Appl. 39(17), 13051–13069 (2012).  https://doi.org/10.1016/j.eswa.2012.05.056CrossRefGoogle Scholar
  3. 3.
    Brock, M., Goscinski, A.: Toward ease of discovery, selection and use of clusters within a cloud. In: 2010 IEEE 3rd International Conference on Cloud Computing, pp. 289–296, July 2010Google Scholar
  4. 4.
    Ciuffoletti, A.: Application level interface for a cloud monitoring service. Comput. Stand. Interfaces 46, 15–22 (2016). http://www.sciencedirect.com/science/article/pii/S0920548916000027CrossRefGoogle Scholar
  5. 5.
    Docker: Docker Containers (2013). https://www.docker.com/. Accessed 25 Oct 2016
  6. 6.
    Docker: Docker Machine Drivers (2017). https://docs.docker.com/machine/drivers/. Accessed 1 Aug 2017
  7. 7.
    Docker: Try Swarm at scale (2017). https://docs.docker.com/swarm/swarm_at_scale/about/. Accessed 1 Aug 2017
  8. 8.
    Docker, S.: Docker Swarm (2017). https://docs.docker.com/engine/swarm/. Accessed 29 May 2017
  9. 9.
    Flocker: FLOCKER (2016). https://clusterhq.com/flocker/introduction/. Accessed 29 Dec 2016
  10. 10.
    Hadley, J., Elkhatib, Y., Blair, G., Roedig, U.: MultiBox: lightweight containers for vendor-independent multi-cloud deployments. In: Horne, R. (ed.) EGC 2015. CCIS, vol. 514, pp. 79–90. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-25043-4_8CrossRefGoogle Scholar
  11. 11.
    Han, S.M., Hassan, M.M., Yoon, C.W., Huh, E.N.: Efficient service recommendation system for cloud computing market. In: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human, ICIS 2009, pp. 839–845. ACM, New York (2009). http://doi.acm.org/10.1145/1655925.1656078
  12. 12.
    Jia, Q., Shen, Z., Song, W., van Renesse, R., Weatherspoon, H.: Supercloud: opportunities and challenges. SIGOPS Oper. Syst. Rev. 49(1), 137–141 (2015). http://doi.acm.org/10.1145/2723872.2723892CrossRefGoogle Scholar
  13. 13.
    Kratzke, N.: Smuggling multi-cloud support into cloud-native applications using elastic container platforms. In: Proceedings of the 7th International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, pp. 57–70. INSTICC, SciTePress (2017)Google Scholar
  14. 14.
    Kratzke, N., Quint, P.C.: About automatic benchmarking of IaaS cloud service providers for a world of container clusters. J. Cloud Comput. Res. 1(1), 16–34 (2015)Google Scholar
  15. 15.
    Leitner, P., Cito, J.: Patterns in the chaos & mdash; a study of performance variation and predictability in public IaaS clouds. ACM Trans. Internet Technol. 16(3), 15:1–15:23 (2016). http://doi.acm.org/10.1145/2885497
  16. 16.
    Li, A., Yang, X., Kandula, S., Zhang, M.: CloudCMP: comparing public cloud providers. In: Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement, IMC 2010, pp. 1–14. ACM, New York (2010). http://doi.acm.org/10.1145/1879141.1879143
  17. 17.
    Li, W., Tordsson, J., Elmroth, E.: Modeling for dynamic cloud scheduling via migration of virtual machines. In: Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and Science, CLOUDCOM 2011, pp. 163–171. IEEE Computer Society, Washington, DC (2011).  https://doi.org/10.1109/CloudCom.2011.31
  18. 18.
    Li, Z., OBrien, L., Zhang, H.: CEEM: a practical methodology for cloud services evaluation. In: 2013 IEEE Ninth World Congress on Services, pp. 44–51, June 2013Google Scholar
  19. 19.
    Li, Z., O’Brien, L., Zhang, H., Cai, R.: On a catalogue of metrics for evaluating commercial cloud services. In: 2012 ACM/IEEE 13th International Conference on Grid Computing, pp. 164–173, September 2012Google Scholar
  20. 20.
    Meng, S., Liu, L.: Enhanced monitoring-as-a-service for effective cloud management. IEEE Trans. Comput. 62(9), 1705–1720 (2013)MathSciNetCrossRefGoogle Scholar
  21. 21.
    PORTWORX: The Solution for Stateful Containers in Production. Designed for DevOps (2017). https://portworx.com/. Accessed 16 Aug 2017
  22. 22.
    Ravello: Ravello Systems: Virtual Labs Using Nested Virtualization (2016). https://www.ravellosystems.com. Accessed 15 Nov 2016
  23. 23.
    Razavi, K., Ion, A., Tato, G., Jeong, K., Figueiredo, R., Pierre, G., Kielmann, T.: Kangaroo: a tenant-centric software-defined cloud infrastructure. In: 2015 IEEE International Conference on Cloud Engineering (IC2E), pp. 106–115, March 2015Google Scholar
  24. 24.
    ur Rehman, Z., Hussain, O.K., Hussain, F.K.: Multi-criteria IaaS service selection based on QoS history. In: 2013 IEEE 27th International Conference on Advanced Information Networking and Applications (AINA), pp. 1129–1135, March 2013Google Scholar
  25. 25.
    ur Rehman, Z., Hussain, O.K., Chang, E., Dillon, T.: Decision-making framework for user-based inter-cloud service migration. Electron. Commerce Res. Appl. 14(6), 523–531 (2015). http://www.sciencedirect.com/science/article/pii/S1567422315000575CrossRefGoogle Scholar
  26. 26.
    Rehman, Z.U., Hussain, O.K., Hussain, F.K.: Parallel cloud service selection and ranking based on QoS history. Int. J. Parallel Program. 42(5), 820–852 (2014).  https://doi.org/10.1007/s10766-013-0276-3CrossRefGoogle Scholar
  27. 27.
    REX-RAY: Rex-ray container storage management (2017). http://rexray.readthedocs.io/en/stable/. Accessed 16 Aug 2017
  28. 28.
    Roy, B.: The outranking approach and the foundations of electre methods. Theory Decis. 31(1), 49–73 (1991).  https://doi.org/10.1007/BF00134132MathSciNetCrossRefGoogle Scholar
  29. 29.
    Docker Samples: Voting Application (2017). https://github.com/dockersamples/example-voting-app. Accessed 12 Aug 2017
  30. 30.
    Scheuner, J., Leitner, P., Cito, J., Gall, H.C.: Cloud workbench - infrastructure-as-code based cloud benchmarking. CoRR abs/1408.4565 (2014). http://arxiv.org/abs/1408.4565
  31. 31.
    Shen, Z., Jia, Q., Sela, G.E., Rainero, B., Song, W., van Renesse, R., Weatherspoon, H.: Follow the sun through the clouds: application migration for geographically shifting workloads. In: Proceedings of the Seventh ACM Symposium on Cloud Computing, SoCC 2016, pp. 141–154. ACM, New York (2016). http://doi.acm.org/10.1145/2987550.2987561
  32. 32.
    Silas, S., Rajsingh, E.B., Ezra, K.: Efficient service selection middleware using electre methodology for cloud environments. Inf. Technol. J. 11(7), 868 (2012)CrossRefGoogle Scholar
  33. 33.
    Silva-Lepe, I., Subramanian, R., Rouvellou, I., Mikalsen, T., Diament, J., Iyengar, A.: SOAlive service catalog: a simplified approach to describing, discovering and composing situational enterprise services. In: Bouguettaya, A., Krueger, I., Margaria, T. (eds.) ICSOC 2008. LNCS, vol. 5364, pp. 422–437. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-89652-4_32CrossRefGoogle Scholar
  34. 34.
    Williams, D., Jamjoom, H., Weatherspoon, H.: The xen-blanket: virtualize once, run everywhere. In: Proceedings of the 7th ACM European Conference on Computer Systems, EuroSys 2012, pp. 113–126. ACM, New York (2012). http://doi.acm.org/10.1145/2168836.2168849

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Esha Barlaskar
    • 1
  • Peter Kilpatrick
    • 1
  • Ivor Spence
    • 1
  • Dimitrios S. Nikolopoulos
    • 1
  1. 1.The School of Electronics, Electrical Engineering and Computer ScienceQueen’s University BelfastBelfastUK

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