Performance Characterization and Profiling of Chained CPU-bound Virtual Network Functions

The increased demand for high-quality Internet connectivity resulting from the growing number of connected devices and advanced services has put significant strain on telecommunication networks. In response, cutting-edge technologies such as Network Function Virtualization (NFV) and Software Defined Networking (SDN) have been introduced to transform network infrastructure. These innovative solutions offer dynamic, efficient, and easily manageable networks that surpass traditional approaches. To fully realize the benefits of NFV and maintain the performance level of specialized equipment, it is critical to assess the behavior of Virtual Network Functions (VNFs) and the impact of virtualization overhead. This paper delves into understanding how various factors such as resource allocation, consumption, and traffic load impact the performance of VNFs. We aim to provide a detailed analysis of these factors and develop analytical functions to accurately describe their impact. By testing VNFs on different testbeds, we identify the key parameters and trends, and develop models to generalize VNF behavior. Our results highlight the negative impact of resource saturation on performance and identify the CPU as the main bottleneck. We also propose a VNF profiling procedure as a solution to model the observed trends and test more complex VNFs deployment scenarios to evaluate the impact of interconnection, co-location, and NFV infrastructure on performance

Admission Control and Virtual Network Embedding in 5G Networks: A Deep Reinforcement-Learning Approach

Fifth-generation (5G) networks are already available in major urban areas and are expected to bring a major transformation to citizens' lives. 5G services, such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), and massive machine-type communications (mMTC), require a network infrastructure capable of supporting stringent requirements in terms of latency and bandwidth demands; as such, it must be highly dynamic and flexible. Network slicing is a key enabler technology that can provide dynamic and flexible characteristics to 5G network architecture. A network slice (NS) can be defined as a partition of network and IT resources, that is, network links and nodes capacity dedicated to a specific set of service demands. As a result, different NSs can coexist over the same physical infrastructure network and can be used to dynamically and flexibly deploy the aforementioned 5G services. However, to efficiently implement NSs with different requirements, communication service providers (CSPs) that own the physical infrastructure network must adopt sophisticated techniques for admission control and resource allocation of NSs. In this paper, we present a novel framework for admission control and resource allocation of 5G NSs in metro-core networks. Specifically, our framework is based on a deep reinforcement learning (DRL) algorithm called Advantage Actor Critic (A2C), which performs admission control, i.e. it is capable of learning which slice to admit based on the availability of the physical network resources. Then, given the diversity of requirements for each 5G service, we propose different resource allocation algorithms based on integer linear programming (ILP) and heuristics to treat each service accordingly. Results show that our proposed framework can increase the number of admitted NSs with respect to the case in which the admission control is disabled by improving the resource allocation performance

Escalamento dinâmico de frequência da CPU usando aprendizado de máquina em aplicações NFV.

Growth in the Information and Communication Technology sector is increasing the need to improve the quality of service and energy efficiency, as this industry has already surpassed 12% of global energy consumption in 2017. Data centers correspond to a large part of this consumption, accounting for about 15% of energy expenditure on the Information and Communication Technology domain; moreover, the subsystem that generates the most costs for data center operators is that of servers and storage. Many solutions have been proposed to reduce server consumption, such as the use of dynamic voltage and frequency scaling, a technology that enables the adaptation of energy consumption to the workload by modifying the operating voltage and frequency, although they are not optimized for network traffic. In this thesis, a control method was developed using a prediction engine based on the analysis of the ongoing traffic. Machine learning algorithms based on Neural Networks and Support Vector Machines have been used, and it was verified that it is possible to reduce power consumption by up to 12% on servers with Intel Sandy Bridge processor and up to 21 % in servers with Intel Haswell processor when compared to the maximum frequency, which is currently the most used solution in the industry.O crescimento do setor de Tecnologia da Informação e Comunicação está aumentando a necessidade de melhorar a qualidade de serviço e a eficiência energética, pois o setor já ultrapassou a marca de 12% do consumo energético global em 2017. Data centers correspondem a grande parte desse consumo, representando cerca de 15% dos gastos com energia do setor Tecnologia Informação e Comunicação; além disso, o subsistema que gera mais custos para operadores de data centers é o de servidores e armazenamento. Muitas soluções foram propostas a fim de reduzir o consumo de energia com servidores, como o uso de escalonamento dinâmico de tensão e frequência, uma tecnologia que permite adaptar o consumo de energia à carga de trabalho, embora atualmente não sejam otimizadas para o processamento do tráfego de rede. Nessa dissertação, foi desenvolvido um método de controle usando um mecanismo de previsão baseado na análise do tráfego que chega aos servidores. Os algoritmos de aprendizado de máquina baseados em Redes Neurais e em Máquinas de Vetores de Suporte foram utilizados, e foi verificado que é possível reduzir o consumo de energia em até 12% em servidores com processador Intel Sandy Bridge e em até 21% em servidores com processador Intel Haswell quando comparado com a frequência máxima, que é atualmente a solução mais utilizada na indústria

SD-WAN: how the control of the network can be shifted from core to edge

Wide Area Network (WAN) reliability has become an imperative for enterprises with Cloud-hosted applications and distributed branch offices. Many solutions and different network technologies have been proposed over the years, such as leased lines, frame relay, or Multi-Protocol Label Switching (MPLS). Those solutions offer Quality of Service (QoS) at costs that are too high for companies today. Software-Defined Wide Area Network (SD-WAN) is regarded as the promising technological solution for the next generation of enterprise networks, since it is capable of increasing network reliability and agility while reducing costs. In this paper, we provide an overview of this technology, addressing its advantages and research opportunities

Performance Evaluation of Overlay Networking for delay-sensitive services in SD-WAN

A reliable Wide Area Network (WAN) has become an imperative need for enterprises with Cloud-hosted applications and distributed branch offices. Software-Defined Wide Area Network (SD-WAN) has been regarded as the most promising technological solution for next generation enterprise networks capable of increasing network agility and reducing costs. In this paper, we present an experimental SD-WAN solution capable of running and optimizing delay-sensitive services, such as VoIP and video streaming, while minimizing downtime caused by network failures. We validate our solution thanks to two SD-WAN testbeds: the first one is deployed in a municipal network of an Italian city, while the other is emulated in our laboratory. The goal is to show the capability of SD-WAN of guaranteeing fast recovery and resilience in case of network failures, exploiting an innovative eBPF-based monitoring technique

Resiliency in SD-WAN with eBPF Monitoring: Municipal Network and Video Streaming Use Cases

A reliable Wide Area Network (WAN) has become an imperative business for enterprises with Cloud-hosted applications and distributed branch offices. Software-Defined Wide Area Networking (SD-WAN) has been regarded as the promising technological solution for next generation enterprise networks capable of increasing network agility and reducing costs. In this demonstration, we present two SD-WAN testbeds: the first one is deployed in a municipal network of an Italian city, while the other is emulated in our laboratory. The goal is to show the capability of SD-WAN to guarantee service availability and resiliency in case of network failures, exploiting an innovative eBPF-based monitoring technique

Reconfiguration of VNF Placement in an Optical Metro Network by a Modular Planning Tool

We demonstrate the recurrent reconfiguration of virtual network function placement and routing and wavelength assignment in optical metro networks supporting 5G services. Reconfiguration solutions are provided by a dedicated planning-tool module

On the Network Slicing for Enterprise Services with Hybrid SDN

Nowadays, companies strongly rely on Virtual Private Networks (VPNs) to deliver services between geographically distributed branch offices. Internet Service Providers (ISPs) must therefore offer a reliable and cost-effective connectivity solution. VPNs are commonly based on static bandwidth allocation over MPLS tunnels, which cause over-provisioning and underutilization of network resources. Software Defined Networking (SDN) appears as a solution to provide agile enterprise networking while reducing operators cost. This paper presents the design and implementation of a Hybrid SDN-based network application to provide dynamic services. Such an architecture enables combining centralized and distributed control with traditional VPN protocols to provision services through network slices. The application performs a flexible policy-based routing, selecting the access technology according to the Quality of Service (QoS) requirements and the network conditions. The simulations executed over an VIRL emulated environment by Cisco show that the proposed network control enables the services to be efficiently provisioned without the need of over-provisioning the resources. Furthermore, a customized network slicing over legacy equipment guarantees the service requirements

Portable MiniLab for Hands-on Experimentation with Software Defined Networking

The new paradigms brought to the networking area by softwarization, not only are revolutionizing research and industry, but start deeply impacting on teaching. While in the past most of education in basic networking relied upon studying theory and learning standard protocols, today the hands-on experience is gaining paramount importance. In this paper, after briefly explaining how SDN changed the learning experience, we present a portable, low-cost, self-contained hardware laboratory to experiment with real SDN networks based on OpenFlow switches, valuable for both teaching and research. We then show some use-case that can be investigated within possible projects developed using this testbed. Though devised mainly for SDN, we will show that this testbed can support experimentation also of traditional switching concepts, such as packet classification. Finally, we introduce a short demonstration that can be presented live at the conference