Intelligent Network Service Optimization in the Context of 5G/NFV

Abstract

Our contemporary society has never been more connected and aware of vital information in real time, through the use of innovative technologies. A considerable number of applications have transitioned into the cyber-physical domain, automating and optimizing their routines and processes via the dense network of sensing devices and the immense volumes of data they collect and instantly share. In this paper, we propose an innovative architecture based on the monitoring, analysis, planning, and execution (MAPE) paradigm for network and service performance optimization. Our study confirms distinct evidence that the utilization of learning algorithms, consuming datasets enriched with the users’ empirical opinions as input during the analysis and planning phases, contributes greatly to the optimization of video streaming quality, especially by handling different packet loss rates, paving the way for the achievable provision of a resilient communications platform for calamity assessment and management.

Path Enumeration Solution for Evaluating Reliability, Based on the Path Algebra Framework

“…Notwithstanding, Next-Generation (NG) environments like 5G, 6G, and beyond, push the boundaries of the industry even further [9][10][11]. NGN versatility brings a wealth of mission-critical applications to the end user like never before.…”

Leveraging Network Data Analytics Function and Machine Learning for Data Collection, Resource Optimization, Security and Privacy in 6G Networks

“…NWDAF can be combined with additional key enabling technologies in fifth-generation (5G) networks, such as open radio access network (O-RAN) which also supports closed loop automation via ML [23]- [25]. NWDAF is based on network function virtualization (NFV), which is a key supporting technology in beyond 5G (B5G) networks [26]- [28]. In this context, basic network operations and hardware elements are replaced by virtual machines, allowing more flexible network deployments, due to the hardware decoupling capabilities offered by NFV.…”

A Link-Layer Virtual Networking Solution for Cloud-Native Network Function Virtualisation Ecosystems: L2S-M

“…This is an important step towards the integration of NFV in microservice platforms since the management of VLs (usually represented as virtual networks) is a fundamental aspect for the effective deployment of NSes, as seen in works like [29], where the authors perform a comprehensive analysis of NFV systems and deployments, or [30], where the authors explain in detail the use of virtual networking and its performance impact depending on the virtual link types. In this regard, the interest of the research community in closing the gap between NFV and microservice platforms can be seen in such works as [31], where the authors propose an architecture based on the monitoring, analysis, planning, and execution (MAPE) paradigm for the optimisation of network service performance to guarantee quality of service (QoS) in NFV environments, including container-based solutions, such as Docker and Kubernetes. Similarly, another example of this effort can be seen in the work [32], where authors propose an implementation of a novel framework that enables the optimal deployment of contained-based VNFs, using a multi-layer approach based on monitoring and analysing data from the physical, virtual and service layers.…”