The main issue related to Software-Defined Network emulators is how to replicate real behavior in experiments. Mininet and others SDN emulators have an architecture that limits both the scope of experiments and the fidelity of networking tests. Consequently, the serialization, contention, and load of background processes may produce delays that compromise the operation of events such as transmitting a packet or completing a computation, possibly invalidating the performance evaluation of a network emulation. To address these problems, this paper presents vSDNEmul, a network emulator based on Docker container virtualization. Different from Mininet, vSDNEmul isolates each node in a container and interconnects the nodes through virtual or tunnel links. By using containers, vSDNEmul allows autonomous and flexible creation of independent network elements, resulting in more realistic emulations. This paper reports performance evaluations comparing vSDNEmul and Mininet. The results obtained with the vSDNEmul emulator are more realistic and present higher accuracy.

Caching plays a central role in networked systems, reducing the load on servers and the delay experienced by users. Despite their relevance, networked caching systems still pose a number of challenges pertaining their long term behavior. In this paper, we formally show and experimentally evidence conditions under which networked caches tend to synchronize over time. Such synchronization, in turn, leads to performance degradation and aging, motivating the monitoring of caching systems for eventual rejuvenation, as well as the deployment of diverse cache replacement policies across caches to promote diversity and preclude synchronization and its aging effects. Based on trace-driven simulations with real workloads, we show how hit probability is sensitive to varying channel reliability, cache sizes, and cache separation, indicating that the mix of simple policies, such as Least Recently Used (LRU) and Least Frequently Used (LFU), provide competitive performance against state-of-art policies. Indeed, our results suggest that diversity in cache replacement policies, rejuvenation and intentional dropping of requests are strategies that build diversity across caches, preventing or mitigating performance degradation due to caching aging.

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP’s proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.

Network slicing (NS) is becoming an essential element of service management and orchestration in communication networks, starting from mobile cellular networks and extending to a global initiative. NS can reshape the deployment and operation of traditional services, support the introduction of new ones, vastly advance how resource allocation performs in networks, and notably change the user experience. Most of these promises still need to reach the real world, but they have already demonstrated their capabilities in many experimental infrastructures. However, complexity, scale, and dynamism are pressuring for a Machine Learning (ML)-enabled NS approach in which autonomy and efficiency are critical features. This trend is relatively new but growing fast and attracting much attention. This article surveys Artificial Intelligence-enabled NS and its potential use in current and future infrastructures. We have covered state-of-the-art ML-enabled NS for all network segments and organized the literature according to the phases of the NS life cycle. We also discuss challenges and opportunities in research on this topic.

O paradigma de redes definidas por software (SDN) está sendo investigado como a solução mais promissora para o atual engessamento da internet, uma vez que propõe a dissociação entre o plano de dados e o plano de controle, proporcionando maior programabilidade às redes de computadores. No entanto, ainda há lacunas em serviços disponíveis nessa arquitetura, dentre as quais se observa o serviço de cálculos de caminhos, que não está evoluindo consideravelmente entre os controladores. Por exemplo, a reserva de recursos, a partir dos requisitos necessários de cada aplicação, permanece como um desafio a ser vencido. Este artigo apresenta uma estratégia de cálculo de caminhos para redes SDN. O objetivo é oferecer um serviço mais flexível no estabelecimento de fluxos OpenFlow, além de possibilitar restrições determinísticas de qualidade vindas das aplicações. A proposta contribui também com uma arquitetura que pode ser aplicada a controladores SDN, um algoritmo de busca, baseado em uma métrica de qualidade de serviço (QoS), e uma análise de desempenho, mostrando que o algoritmo é capaz de minimizar o tempo de busca, processamento e consumo de memória pelo controlador na rede SDN.

The combination of Network Function Virtualization (NFV) and Software Defined Networking (SDN) can improve the control and utilization of network resources. However, this issue still requires proper solutions to virtualize large-scale networks, which would allow the use of SDN and Virtualization in real environments.Thus, this paper proposes a virtualization architecture for SDN that relies on a proxy-based approach. The NVP (Network Virtualization Proxy) is a virtualization proxy that intercepts messages exchanged between controllers and switches SDN enabling network virtualization. An implementation of the proposal was developed as a proof of concept and load testing was performed showing that the solution can provide network virtualization in a scalable manner, using less than 2.5 MB of memory to manage 100 switches performing simultaneous requests, whereas FlowVisor requires more than 200 MB.