The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Data Mining and Forecasting in Large-Scale Telecommunication Networks
IEEE Expert: Intelligent Systems and Their Applications
Constructing Bayesian Networks to Predict Uncollectible Telecommunications Accounts
IEEE Expert: Intelligent Systems and Their Applications
Proactive Network Fault Detection
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
BBN-based software project risk management
Journal of Systems and Software - Special issue: Applications of statistics in software engineering
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Introduction to Machine Learning (Adaptive Computation and Machine Learning)
Rule Based Reasoning for Network Management
CAMP '05 Proceedings of the Seventh International Workshop on Computer Architecture for Machine Perception
Automated Traffic Classification and Application Identification using Machine Learning
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Network Management Challenges for Next Generation Networks
LCN '05 Proceedings of the The IEEE Conference on Local Computer Networks 30th Anniversary
Scalable Network Management Using Lightweight Programmable Network Services
Journal of Network and Systems Management
Adaptive distributed monitoring with accuracy objectives
Proceedings of the 2006 SIGCOMM workshop on Internet network management
ACM SIGCOMM Computer Communication Review
Network Management Fundamentals
Network Management Fundamentals
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Application of Bayesian Networks to Architectural Optimisation
ECBS '07 Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems
Proceedings of the 2007 workshop on Service-oriented computing performance: aspects, issues, and approaches
Research on an Integrated Network Management System
SNPD '07 Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
A survey of techniques for internet traffic classification using machine learning
IEEE Communications Surveys & Tutorials
Towards Autonomic Network Management: an Analysis of Current and Future Research Directions
IEEE Communications Surveys & Tutorials
A bayesian network approach to traffic flow forecasting
IEEE Transactions on Intelligent Transportation Systems
Application of Bayesian Belief Network in Reliable Analysis for Video Deinterlacing
IEEE Transactions on Consumer Electronics
Control and management in next-generation networks: challenges and opportunities
IEEE Communications Magazine
Realization of the next-generation network
IEEE Communications Magazine
Key research challenges in network management
IEEE Communications Magazine
IEEE Communications Magazine
IEEE Journal on Selected Areas in Communications - Part Supplement
A probabilistic approach to fault diagnosis in linear lightwave networks
IEEE Journal on Selected Areas in Communications
Bayesian Neural Networks for Internet Traffic Classification
IEEE Transactions on Neural Networks
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The ever evolving telecommunication networks in terms of their technology, infrastructure, and supported services have always posed challenges to the network managers to come up with an efficient Network Management System (NMS) for effective network management. The need for automated and efficient management of the current networks, more specifically the Next Generation Network (NGN), is the subject addressed in this research. A detailed description of the management challenges in the context of current networks is presented and then this work enlists the desired features and characteristics of an efficient NMS. It then proposes that there is a need to apply Artificial Intelligence (AI) and Machine Learning (ML) approaches for enhancing and automating the functions of NMS. The first contribution of this work is a comprehensive survey of the AI and ML approaches applied to the domain of NM. The second contribution of this work is that it presents the reasoning and evidence to support the choice of Bayesian Networks (BN) as a viable solution for ML-based NMS. The final contribution of this work is that it proposes and implements three novel NM solutions based on the BN approach, namely BN-based Admission Control (BNAC), BN-based Distributed Admission Control (BNDAC) and BN-based Intelligent Traffic Engineering (BNITE), along with the description of algorithms underpinning the proposed framework.