Chapter

Knowledge Science, Engineering and Management

Volume 6291 of the series Lecture Notes in Computer Science pp 518-529

Knowledge Discovery Using Bayesian Network Framework for Intelligent Telecommunication Network Management

  • Abul BasharAffiliated withSchool of Computing and Engineering, University of Ulster
  • , Gerard ParrAffiliated withSchool of Computing and Engineering, University of Ulster
  • , Sally McCleanAffiliated withSchool of Computing and Engineering, University of Ulster
  • , Bryan ScotneyAffiliated withSchool of Computing and Engineering, University of Ulster
  • , Detlef NauckAffiliated withResearch and Technology, British Telecom

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Abstract

The ever-evolving nature of telecommunication networks has put enormous pressure on contemporary Network Management Systems (NMSs) to come up with improved functionalities for efficient monitoring, control and management. In such a context, the rapid deployments of Next Generation Networks (NGN) and their management requires intelligent, autonomic and resilient mechanisms to guarantee Quality of Service (QoS) to the end users and at the same time to maximize revenue for the service/network providers. We present a framework for evaluating a Bayesian Networks (BN) based Decision Support System (DSS) for assisting and improving the performance of a Simple Network Management Protocol (SNMP) based NMS. More specifically, we describe our methodology through a case study which implements the function of Call Admission Control (CAC) in a multi-class video conferencing service scenario. Simulation results are presented for a proof of concept, followed by a critical analysis of our proposed approach and its application.

Keywords

Next Generation Networks (NGN) Network Management Bayesian Networks (BN) Call Admission Control (CAC)