Use of a virtualization in the transition of a telecommunication networks toward 5G

We are in the front of the next big step of a new generation of the telecommunications networks, called 5G. The 5G in still in the preparation, but the actual wide spread use is nearby. The move toward 5G is not possible without use of a cloud and a virtualization. In the paper we are dealing with the issues how to incorporate existing fixed networks to the mobile 5G network and how to use a virtualization technology when moving to 5G. From the example of a real telecommunication system we defined issues, dilemmas and suggestions when moving toward 5G networks using virtualization

Transforming Large-Scale Virtualized Networks: Advancements in Latency Reduction, Availability Enhancement, and Security Fortification

In today’s digital age, the increasing demand for networks, driven by the proliferation of connected devices, data-intensive applications, and transformative technologies, necessitates robust and efficient network infrastructure. This thesis addresses the challenges posed by virtualization in 5G networking and focuses on enhancing next-generation Radio Access Networks (RANs), particularly Open-RAN (O-RAN). The objective is to transform virtualized networks into highly reliable, secure, and latency-aware systems. To achieve this, the thesis proposes novel strategies for virtual function placement, traffic steering, and virtual function security within O-RAN. These solutions utilize optimization techniques such as binary integer programming, mixed integer binary programming, column generation, and machine learning algorithms, including supervised learning and deep reinforcement learning. By implementing these contributions, network service providers can deploy O-RAN with enhanced reliability, speed, and security, specifically tailored for Ultra-Reliable and Low Latency Communications use cases. The optimized RAN virtualization achieved through this research unlocks a new era in network architecture that can confidently support URLLC applications, including Autonomous Vehicles, Industrial Automation and Robotics, Public Safety and Emergency Services, and Smart Grids

Sidecar based resource estimation method for virtualized environments

The widespread use of virtualization technologies in telecommunication system resulted in series of benefits, as flexibility, agility and increased resource usage efficiency. Nevertheless, the use of Virtualized Network Functions (VNF) in virtualized modules (e.g., containers, virtual machines) also means that some legacy mechanisms that are crucial for a telco grade operation are no longer efficient. Specifically, the monitoring of the resource sets (e.g., CPU power, memory capacity) allocated to VNFs cannot rely anymore on the methods developed for earlier deployment scenarios. Even the recent monitoring solutions designed for cloud environments is rendered useless if the VNF vendor and the telco solution supplier has to deploy its product into a virtualized environment, since it does not have access to the host level monitoring tools. In this paper we propose a sidecar-based solution to evaluate the resources available for a virtualized process. We evaluated the accuracy of our proposal in a proof of concept deployment, using KVM, Docker and Kubernetes virtualization technologies, respectively. We show that our proposal can provide real monitoring data and discuss its applicability

Network Function Virtualization Technology Adoption Strategies

Network function virtualization (NFV) is a novel system adopted by service providers and organizations, which has become a critical organizational success factor. Chief information officers (CIOs) aim to adopt NFV to consolidate and optimize network processes unavailable in conventional methods. Grounded in the diffusion of innovation theory (DOI), the purpose of this multiple case research study was to explore strategies chief information officers utilized to adopt NFV technology. Participants include two CIOs, one chief security information officer (CSIO), one chief technical officer (CTO), and two senior information technology (IT) executives. Data were collected through semi-structured telephone interviews and eight organizational documents. Through thematic analysis, four significant themes became apparent: organizational awareness, no hindrances to NFV technology adoption, documentation and implementation plan, and operational costs and efficiency. A key recommendation is for CIOs, CSIOs, CTOs, and senior IT managers to adopt the capability to document globally accepted processes and procedures for seamless adoption of NFV technology. The implications for positive social change include the potential to reduce energy consumption, preserving natural resources, and reducing environmental pollution due to the emission of dangerous gases that cause environmental degradation

Managing Distributed Cloud Applications and Infrastructure

The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum. The scale and complexity is simply so complex that it is no longer realistic for IT teams to manually foresee the potential issues and manage the dynamism and dependencies across an increasing inter-dependent chain of service provision. This Open Access Pivot explores these challenges and offers a solution for the intelligent and reliable management of physical infrastructure and the optimal placement of applications for the provision of services on distributed clouds. This book provides a conceptual reference model for reliable capacity provisioning for distributed clouds and discusses how data analytics and machine learning, application and infrastructure optimization, and simulation can deliver quality of service requirements cost-efficiently in this complex feature space. These are illustrated through a series of case studies in cloud computing, telecommunications, big data analytics, and smart cities

Managing Distributed Cloud Applications and Infrastructure

The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum. The scale and complexity is simply so complex that it is no longer realistic for IT teams to manually foresee the potential issues and manage the dynamism and dependencies across an increasing inter-dependent chain of service provision. This Open Access Pivot explores these challenges and offers a solution for the intelligent and reliable management of physical infrastructure and the optimal placement of applications for the provision of services on distributed clouds. This book provides a conceptual reference model for reliable capacity provisioning for distributed clouds and discusses how data analytics and machine learning, application and infrastructure optimization, and simulation can deliver quality of service requirements cost-efficiently in this complex feature space. These are illustrated through a series of case studies in cloud computing, telecommunications, big data analytics, and smart cities

Research challenges in nextgen service orchestration

Fog/edge computing, function as a service, and programmable infrastructures, like software-defined networking or network function virtualisation, are becoming ubiquitously used in modern Information Technology infrastructures. These technologies change the characteristics and capabilities of the underlying computational substrate where services run (e.g. higher volatility, scarcer computational power, or programmability). As a consequence, the nature of the services that can be run on them changes too (smaller codebases, more fragmented state, etc.). These changes bring new requirements for service orchestrators, which need to evolve so as to support new scenarios where a close interaction between service and infrastructure becomes essential to deliver a seamless user experience. Here, we present the challenges brought forward by this new breed of technologies and where current orchestration techniques stand with regards to the new challenges. We also present a set of promising technologies that can help tame this brave new world

On the design of a cost-efficient resource management framework for low latency applications

The ability to offer low latency communications is one of the critical design requirements for the upcoming 5G era. The current practice for achieving low latency is to overprovision network resources (e.g., bandwidth and computing resources). However, this approach is not cost-efficient, and cannot be applied in large-scale. To solve this, more cost-efficient resource management is required to dynamically and efficiently exploit network resources to guarantee low latencies. The advent of network virtualization provides novel opportunities in achieving cost-efficient low latency communications. It decouples network resources from physical machines through virtualization, and groups resources in the form of virtual machines (VMs). By doing so, network resources can be flexibly increased at any network locations through VM auto-scaling to alleviate network delays due to lack of resources. At the same time, the operational cost can be largely reduced by shutting down low-utilized VMs (e.g., energy saving). Also, network virtualization enables the emerging concept of mobile edge-computing, whereby VMs can be utilized to host low latency applications at the network edge to shorten communication latency. Despite these advantages provided by virtualization, a key challenge is the optimal resource management of different physical and virtual resources for low latency communications. This thesis addresses the challenge by deploying a novel cost-efficient resource management framework that aims to solve the cost-efficient design of 1) low latency communication infrastructures; 2) dynamic resource management for low latency applications; and 3) fault-tolerant resource management. Compared to the current practices, the proposed framework achieves 80% of deployment cost reduction for the design of low latency communication infrastructures; continuously saves up to 33% of operational cost through dynamic resource management while always achieving low latencies; and succeeds in providing fault tolerance to low latency communications with a guaranteed operational cost