Advanced spatial network metrics for cognitive management of 5G networks

Abstract

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 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. Keywords 5G networks • Topology management • Spatial network metrics • Cognitive management 1 Introduction Network management in the forthcoming fifth-generation (5G) mobile networks is notably influenced by the softwarization of network infrastructures where several hardware components are virtualized and by the multi-tenancy of the network infrastructures where hardware components are shared by different mobile operators. The main motivation of these 5G capabilities is the reduction of both capital and operational costs. 5G virtual network functions (VNFs) can now be deployed automatically and on-demand on the Edge and the Core segments of the 5G network and can be migrated between the computers that belong to the same net-Communicated by V. Loia.

Distributed dual-layer autonomous closed loops for self-protection of 5G/6G IoT networks from distributed denial of service attacks

“…This component is also instantiated in all the machines of the infrastructure: Service and Compute layers of each Edge and Core segments and for each stakeholder. The capabilities and performance of this component are detailed in [32], and a specific use case for the topology information that the component discovers is specified in [33].…”

E2E network slice management framework for 5G multi-tenant networks

“…The provisioning engine will take the coverage information and the technology information available in the NSI (45) and calculate the list of the network interfaces that need to be used for enforcing the NSI to match the indicated coverage and technology using the latest topological information available (46). This set of network interfaces will be used to create a set of network Intents that will compose the plan to be orchestrated to enforce the E2E network slice (47). All these network Intents are sent (48) to the different FCA components of the system (49).…”

“…When this change is detected (58), the real-time follow-me engine will calculate the affected set of interfaces that need to install the network slice and the affected set of interfaces where the network slice needs to be removed (59). This logic has been designed using a path-finding algorithm [46] that iterates the topological information to determine what kind of handover is taking place (60) [47]. It is noted that a handover can happen between gNBs allocated in the same physical machine or in different machines of the name zone or even between different zones, and thus the number of interfaces involved in these handovers is incrementally increased.…”

On the Use of Composite Indicators for Mobile Communications Network Management in Smart Sustainable Cities

“…However, aspects, such as the mobility of 5G users, which depends on human behavior, increase the dynamics of the network (connection to different antennas, for example), complicating its optimal management. Recently, [11] explores the calculation of advanced spatial metrics, which can be combined with other KPIs, in order to create composed metrics that are used to enhance the dynamic placement of services. In the scenario of a smart city with an ultradense deployment of mobile communications networks, a cognitive network management framework is fundamental, in such a way that the monitoring and calculation of real time metrics drive an autonomous decision-making framework.…”

“…In the scenario of a smart city with an ultradense deployment of mobile communications networks, a cognitive network management framework is fundamental, in such a way that the monitoring and calculation of real time metrics drive an autonomous decision-making framework. Reference [11] compiles and classifies references in the field of defining performance metrics to launch autonomous behaviors in cognitive network management. These metrics include KPIs and parameters that are related to resources, network functionalities, wireless, or service metrics.…”