Machine Learning
The Vision of Autonomic Computing
Computer
Toward Trustworthy Software Systems
Computer
Sensing-based opportunistic channel access
Mobile Networks and Applications
Policy-Based Network Management: Solutions for the Next Generation (The Morgan Kaufmann Series in Networking)
International Journal of Communication Systems
K-Nearest Neighbor Finding Using MaxNearestDist
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Discovery of Spectrum Opportunities with MAC-Layer Sensing in Cognitive Radio Networks
IEEE Transactions on Mobile Computing
Neural network-based learning schemes for cognitive radio systems
Computer Communications
Management of networks and services in a composite radio context
IEEE Wireless Communications
Cognitive Wireless Networks {Guest Editorial}
IEEE Wireless Communications
Teamwork and Collaboration in Cognitive Wireless Networks
IEEE Wireless Communications
m@ANGEL: autonomic management platform for seamless cognitive connectivity to the mobile internet
IEEE Communications Magazine
Context-aware semantic discovery for next generation mobile systems
IEEE Communications Magazine
Supporting context-aware mobile applications: an infrastructure approach
IEEE Communications Magazine
Cognitive networks: adaptation and learning to achieve end-to-end performance objectives
IEEE Communications Magazine
Cognitive functionality in next generation wireless networks: standardization efforts
IEEE Communications Magazine
IEEE Standards Supporting Cognitive Radio and Networks, Dynamic Spectrum Access, and Coexistence
IEEE Communications Magazine
Automated network selection in a heterogeneous wireless network environment
IEEE Network: The Magazine of Global Internetworking
The E3 architecture: enabling future cellular networks with cognitive and self-x capabilities
International Journal of Network Management
Evaluation of signalling loads in a cognitive network management architecture
International Journal of Network Management
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Beyond 3rd Generation (B3G) wireless communication systems are comprised from different Radio Access Technologies (RATs) in order to satisfy all user needs in services. The coexistence of many RATs in the same environment needs advanced network management systems in order to ensure efficient resources utilization while achieving the best possible Quality of Service (QoS) levels. Management functionality in the B3G era will have to solve complex problems, due to the existence of versatile options for satisfying stringent requirements, under difficult environment conditions. The introduction of cognitive systems in the B3G world is a direction for addressing the complexity, as it will enable reaching decisions faster and more reliably, by considering also knowledge and experience derived from past interactions of the system with the network environment. Our work presents an approach for identifying whether a context, encountered by the network segment, has also been dealt in the past. In this case context knowledge can be exploited for fast and cost efficient network reconfiguration and adaptation to the environment conditions.