Management-Based License Discovery for the Cloud

  • Minkyong Kim
  • Han Chen
  • Jonathan Munson
  • Hui Lei
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7636)


Enterprise software is typically licensed through contracts that require organizations to monitor their own usage of the software and purchase the number or amount of licenses required by the vendor’s terms and conditions for that software. Vendors reserve the right to audit an organization’s use of their software, and if an organization is under-licensed, costly back-payments may be required. For this reason, organizations go to great expense to maintain a complete and accurate inventory of their software so that they know their license obligations. The cloud, as an environment offering both greater flexibility in, and a higher degree of control over, an enterprise’s computing infrastructure, presents both new challenges for license compliance as well as new opportunities. In this paper, we introduce a new approach to producing accurate software inventories based on capturing the knowledge that is present in cloud management systems at the time of software provisioning and installation. We also demonstrate new capabilities for rule-based alerting and enforcement that are made possible by our approach.


Virtual Machine Query Range Service Selection License Usage Software License 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Gangadharan, G.R., Comerio, M., Truong, H.-L., D’Andrea, V., De Paoli, F., Dustdar, S.: LASS – License Aware Service Selection: Methodology and Framework. In: Bouguettaya, A., Krueger, I., Margaria, T. (eds.) ICSOC 2008. LNCS, vol. 5364, pp. 607–613. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  2. 2.
    Gangadharan, G., D’Andrea, V., Paoli, S., Weiss, M.: Managing license compliance in free and open source software development. Information Systems Frontiers 14, 143–154 (2012)CrossRefGoogle Scholar
  3. 3.
    Giblin, C., Muller, S., Pfitzmann, B.: From regulatory policies to event monitoring rules: Towards model driven compliance automation. Technical reportGoogle Scholar
  4. 4.
  5. 5.
  6. 6.
    Kanaracus, C.: SAP, Rent-a-Center in Battle Over Millions in Fees. CIO (2011),
  7. 7.
    Lamparter, S., Ankolekar, A., Studer, R.: Preference-based selection of highly configurable web services. In: Proc. of the 16th Int. World Wide Web Conference, pp. 1013–1022. ACM Press (2007)Google Scholar
  8. 8.
    Liu, Y., Muller, S., Xu, K.: A static compliance-checking framework for business process models. IBM Systems Journal 46(2), 335–361 (2007)CrossRefGoogle Scholar
  9. 9.
    Reiff-Marganiec, S., Yu, H.Q., Tilly, M.: Service Selection Based on Non-functional Properties. In: Di Nitto, E., Ripeanu, M. (eds.) ICSOC 2007. LNCS, vol. 4907, pp. 128–138. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Rosenberg, S.D.: Software License Compliance: Myth vs. Reality. E-Commerce Times (2008),

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Minkyong Kim
    • 1
  • Han Chen
    • 1
  • Jonathan Munson
    • 1
  • Hui Lei
    • 1
  1. 1.IBM T.J. Watson Research CenterHawthorneUSA

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