Probabilistic Inference for Network Management

  • Jianguo Ding
  • Bernd J. Krämer
  • Yingcai Bai
  • Hansheng Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3262)


As networks grow in size, heterogeneity, and complexity of applications and network services, an efficient network management system needs to work effectively even in face of incomplete management information, uncertain situations and dynamic changes. We use Bayesian networks to model the network management and consider the probabilistic backward inference between the managed entities, which can track the strongest causes and trace the strongest routes between particular effects and its causes. This is the foundation for further intelligent decision of management in networks.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Jianguo Ding
    • 1
    • 2
  • Bernd J. Krämer
    • 2
  • Yingcai Bai
    • 1
  • Hansheng Chen
    • 3
  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiP. R. China
  2. 2.Department of Electrical Engineering and Information EngineeringFernUniversität HagenHagenGermany
  3. 3.East-china Institute of Computer TechnologyShanghaiP. R. China

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