BluePlan: A Service for Automated Migration Plan Construction Using AI

  • Malik Jackson
  • John Rofrano
  • Jinho HwangEmail author
  • Maja Vukovic
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11434)


Migration of legacy applications to Cloud has been growing steadily over the past years, driven by the promise of greater flexibility, scalability, and lower management costs. However, the complexity of the migration tasks and activities makes transformation of the current service and application architectures a long and difficult process that involves months of migration planning and execution. In this paper, we present a service application BluePlan and its implementation, which employs an artificial intelligence (AI) planner that optimizes the end-to-end migration planning with constraints, and creates migration plans for execution. The AI planner service serves to expedite and simplify the migration planning process by defining the clients’ constraints and resources in a simplified format that abstracts the user’s need to hardcode domains and problems. This capability is exposed as a service and evaluated for migration plans for over 500 hundred clients with varying independent memory, cpu and time constraints in the span of a few minutes, thereby enabling migration project manager and migration architects to reason about potential migration plans, and replan as needed.


AI planning Cloud computing Cloud migration 


  1. 1.
    Branch, J.W., Murthy, K., Shwartz, L., Olsson, E., Larsen, R.A.: Bizmap: a framework for mapping business applications to it infrastructure. In: 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 1377–1383 (2015)Google Scholar
  2. 2.
    Herry, H., Anderson, P., Wickler, G.: Automated planning for configuration changes. In: Proceedings of the 25th International Conference on Large Installation System Administration, pp. 5–5. LISA 2011, USENIX Association, Berkeley (2011).
  3. 3.
    Hwang, J.: Computing resource transformation, consolidation and decomposition in hybrid clouds. In: 2015 11th International Conference on Network and Service Management (CNSM), pp. 144–152, November 2015Google Scholar
  4. 4.
    Hwang, J.: Toward beneficial transformation of enterprise workloads to hybrid clouds. IEEE Trans. Netw. Serv. Manag. 13(2), 295–307 (2016)CrossRefGoogle Scholar
  5. 5.
    Hwang, J., Huang, Y.W., Vukovic, M., Jermyn, J.: Cloud transformation analytics services: a case study of cloud fitness validation for server migration. In: 2015 IEEE International Conference on Services Computing, pp. 387–394, June 2015Google Scholar
  6. 6.
    Hwang, J., Vukovic, M., Anerousis, N.: FitScale: scalability of legacy applications through migration to cloud. In: Sheng, Q.Z., Stroulia, E., Tata, S., Bhiri, S. (eds.) ICSOC 2016. LNCS, vol. 9936, pp. 123–139. Springer, Cham (2016). Scholar
  7. 7.
    Jermyn, J., Hwang, J., Bai, K., Vukovic, M., Anerousis, N., Stolfo, S.: Improving readiness for enterprise migration to the cloud. In: Proceedings of the Middleware Industry Track, pp. 5:1–5:7. Industry papers. ACM, New York (2014).
  8. 8.
    Kim, I.K., Zeng, S., Young, C., Hwang, J., Humphrey, M.: A supervised learning model for identifying inactive VMS in private cloud data centers. In: Proceedings of the Industrial Track of the 17th International Middleware Conference, pp. 2:1–2:7. Middleware Industry 2016. ACM, New York (2016).
  9. 9.
    Nidd, M., Bai, K., Hwang, J., Vukovic, M., Tacci, M.: Automated business application discovery. In: 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 794–797, May 2015Google Scholar
  10. 10.
    Vukovic, M., Hwang, J.: Cloud migration using automated planning. In: NOMS 2016–2016 IEEE/IFIP Network Operations and Management Symposium, pp. 96–103, April 2016Google Scholar
  11. 11.
    Wu, D., Hwang, J., Vukovic, M., Anerousis, N.: BlueSight: automated discovery service for cloud migration of enterprises. In: Drira, K., Wang, H., Yu, Q., Wang, Y., Yan, Y., Charoy, F., Mendling, J., Mohamed, M., Wang, Z., Bhiri, S. (eds.) ICSOC 2016. LNCS, vol. 10380, pp. 211–215. Springer, Cham (2017). Scholar
  12. 12.
    Zhang, B., Hwang, J., Ma, L., Wood, T.: Towards security-aware virtual server migration optimization to the cloud. In: 2015 IEEE International Conference on Autonomic Computing, pp. 71–80, July 2015Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Malik Jackson
    • 1
  • John Rofrano
    • 2
  • Jinho Hwang
    • 2
    Email author
  • Maja Vukovic
    • 2
  1. 1.University of Maryland Baltimore CountyBaltimoreUSA
  2. 2.IBM T.J. Watson Research CenterNew YorkUSA

Personalised recommendations