iOn-Profiler: intelligent Online multi-objective VNF Profiling with Reinforcement Learning

no code implementations • 14 Dec 2023 • Xenofon Vasilakos, Shadi Moazzeni, Anderson Bravalheri, Pratchaya Jaisudthi, Reza Nejabati, Dimitra Simeonidou

Leveraging the potential of Virtualised Network Functions (VNFs) requires a clear understanding of the link between resource consumption and performance.

reinforcement-learning Reinforcement Learning (RL)

Adaptive Resource Management for Edge Network Slicing using Incremental Multi-Agent Deep Reinforcement Learning

no code implementations • 26 Oct 2023 • Haiyuan Li, Yuelin Liu, Xueqing Zhou, Xenofon Vasilakos, Reza Nejabati, Shuangyi Yan, Dimitra Simeonidou

At the edge, dynamic computing requests require advanced resource management for adaptive network slicing, including resource allocations, function scaling and load balancing to utilize only the necessary resources in resource-constraint networks.

Edge-computing Incremental Learning +2

Integrated Methodology to Cognitive Network \& Slice Management in Virtualized 5G Networks

no code implementations • 11 May 2020 • Xenofon Vasilakos, Navid Nikaein, Dean H Lorenz, Berkay Koksal, Nasim Ferdosian

To this end, purpose-specific Machine Learning (ML) models can be used to manage and control physical as well as virtual network resources in a way that is fully compliant to slice Service Level Agreements (SLAs), while also boosting the revenue of the underlying physical network operator(s).

Anomaly Detection Management