# Dynamic QoS Management for a Flexible 5G/6G Network Core: A Step toward a Higher Programability
## 1 Introduction  
The development of advanced technologies, new communication types, and the rapid implementation of more intelligent and demanding services, are the leading trends in modern society. The 5G networks have significantly intensified the usage of software technologies, all virtualization techniques, massive MIMO, ultra-densification, and new frequency bands [1] to match these trends. A current research direction has been pursued toward full automation and far more comprehensive implementation of remote management systems. However, 5G still cannot provide satisfactory solutions for many services such as, e.g., multi-sensory holographic teleportation, which requires Tbps data rates and ms latencies. Moreover, it cannot push connectivity density well beyond the 106-km\({}^{2}\) metric (an essential requirement for the upcoming Industry X.0 paradigm) [2]. With all this in mind, the scientific community has defined Key Performance Indicators (KPIs) for the 6G ecosystem [3]. These KPIs will be carefully measured for an efficient transition from a Network-as-an-Infrastructure (Naal) to a Network-as-a-Service architecture (NaaS) [4]. Thus, it is clear that network cloudification intensifies with the critical role of networking in the latest cloud/edge computing technologies, which leads to a convergence of networking and cloud/edge computing [5]. A 6G network should feature a service-based End-to-End (E2E) architecture in which software-defined networking (SDN), network function virtualization (NFV), and network slicing play fundamental roles [6; 7]. These technologies introduce significantly higher programmability into the network and allow the creation of multiple logical networks on a shared physical infrastructure. We expect that they provide higher data rates, enhanced spectral and energy efficiency, better coverage, wide bandwidths, extremely high reliability, ultra-low latency, and dynamic QoS management in all network segments. Dynamic QoS management is essential for achieving high flexibility in available network resource usage. However, in most SDN implementations, a required QoS provides statically, by resource reservation, according to the predefined rules in forwarding engines. Packets map into existing queues with different assigned priorities [8]. Therefore, a lack of dynamic queue management (i.e., the creation, modification, and removal of queues) is evident. Our research focuses on defining and verifying an acceptable method for dynamic QoS. We propose a framework for the 5G/6G network core design, including new service management. It implies service binding into service groups that are most likely offered by the same service provider. Thus, each service group should be a separate slice controlled and managed by its authoritative controller. The dynamic queue management presented in the paper aims to provide dynamic QoS. The central part of the solution is configuring the queues' parameters dynamically according to the requirements specified through the service management on the application layer. Concretely, we use the OVSDB protocol [9] to extend the SDN controller functionality in addition to the features supported by the OpenFlow protocol [10]. Overall, the proposed approach introduces a considerably higher degree of programmability to build a flexible infrastructure (both real and virtual). From the scientific and methodological point of view, it brings the following achievements:  
* Optimized E2E slicing in shared networks across multiple domains;
* Efficient dynamic QoS management in the SDN environment--true dynamic queueing. We have organized the rest of the paper as follows: Section 2 gives a background of core technology. Section 3 reviews the concept of shared networks (Section 3.1) and presents solutions for dynamic QoS management in SDN networks based on the existing literature (Section 3.2). Further, in Section 3.3, we explain the motivation for our study and compare our approach with state-of-the-art research in more detail.