Advanced spatial network metrics for cognitive management of 5G networks

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The emerging Fifth-Generation (5G) mobile networks are empowered by softwarization and programmability, leading to the huge potentials of unprecedented flexibility and capability in cognitive network management such as self-reconfiguration and self-optimization.

To help unlock such potentials, this paper proposes a novel framework that is able to monitor and calculate 5G network topological information in terms of advanced spatial metrics. These metrics, together with enabling and optimization algorithms, are purposely designed to address the complexity of 5G network topologies introduced by network virtualization and infrastructure sharing among operators (multi-tenancy). Consequently, this new framework, centred on a Topology Monitoring Agent (TMA), enables on-demand 5G networks’ spatial knowledge and topological awareness required by 5G cognitive network management in making smart decisions in various autonomous network management tasks including but not limited to Virtual Network Function (VNF) placement strategies. The paper describes several technical use cases enabled by the proposed framework, including Proactive cache allocation, Computation offloading, Node overloading alerting, and Load balancing. Finally, a realistic 5G testbed is deployed with the central component TMA, together with the new spatial metrics and associated algorithms, implemented. Experimental results empirically validate the proposed approach and demonstrate the scalability and performance of the TMA component.
Original languageEnglish
Pages (from-to)215-232
Number of pages18
JournalSoft Computing
Early online date9 Aug 2020
Publication statusPublished - 31 Jan 2021


  • 5G networks
  • topology management
  • spatial network metrics
  • cognitive management


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