Modular architecture providing convergent and ubiquitous intelligent connectivity for networks beyond 2030

The transition of the networks to support forthcoming beyond 5G (B5G) and 6G services introduces a number of important architectural challenges that force an evolution of existing operational frameworks. Current networks have introduced technical paradigms such as network virtualization, programmability and slicing, being a trend known as network softwarization. Forthcoming B5G and 6G services imposing stringent requirements will motivate a new radical change, augmenting those paradigms with the idea of smartness, pursuing an overall optimization on the usage of network and compute resources in a zero-trust environment. This paper presents a modular architecture under the concept of Convergent and UBiquitous Intelligent Connectivity (CUBIC), conceived to facilitate the aforementioned transition. CUBIC intends to investigate and innovate on the usage, combination and development of novel technologies to accompany the migration of existing networks towards Convergent and Ubiquitous Intelligent Connectivity (CUBIC) solutions, leveraging Artificial Intelligence (AI) mechanisms and Machine Learning (ML) tools in a totally secure environment

Augmented In-Band Telemetry to the User Equipment for beyond 5G Converged Packet-Optical Networks

Traffic monitoring through in-band telemetry is extended up to the User Equipment (UE), providing accurate e2e latency measurement. The UE becomes aware of its experienced service performance, enabling autonomous operations for faster automatic source-based Edge-Cloud steering

Extending P4 in-band telemetry to user equipment for latency-and localization-aware autonomous networking with AI forecasting

In beyond-5G networks, detailed end-to-end monitoring of specific application traffic will be required along with the access-backhaul-cloud continuum to enable low latency service due to local edge steering. Current monitoring solutions are confined to specific network segments. In-band network telemetry (INT) technologies for software defined network (SDN) programmable data planes based on the P4 language are effective in the backhaul network segment, although limited to inter-switch latency; therefore, link latencies including wireless and optical segments are excluded from INT monitoring. Moreover, information such as user equipment (UE) geolocation would allow detailed mobility monitoring and improved cloud-edge steering policies. However, the synchronization between latency and location information, typically provided by different platforms, is hard to achieve with current monitoring systems. In this paper, P4-based INT is proposed to be thoroughly extended involving UE. The INT mechanism is designed to provide synchronized and accurate end-to-end latency and geolocation information, enabling decentralized steering policies, i.e., involving UE and selected switches, without SDN controller intervention. The proposal also includes an artificial-intelligence-assisted forecast system able to predict latency and geolocation in advance and trigger faster edge steering

SLA Management in Intent-Driven Service Management Systems: A Taxonomy and Future Directions

Traditionally, network and system administrators are responsible for designing, configuring, and resolving the Internet service requests. Human-driven system configuration and management are proving unsatisfactory due to the recent interest in time-sensitive applications with stringent quality of service (QoS). Aiming to transition from the traditional human-driven to zero-touch service management in the field of networks and computing, intent-driven service management (IDSM) has been proposed as a response to stringent quality of service requirements. In IDSM, users express their service requirements in a declarative manner as intents. IDSM, with the help of closed control-loop operations, perform configurations and deployments, autonomously to meet service request requirements. The result is a faster deployment of Internet services and reduction in configuration errors caused by manual operations, which in turn reduces the service-level agreement (SLA) violations. In the early stages of development, IDSM systems require attention from industry as well as academia. In an attempt to fill the gaps in current research, we conducted a systematic literature review of SLA management in IDSM systems. As an outcome, we have identified four IDSM intent management activities and proposed a taxonomy for each activity. Analysis of all studies and future research directions, are presented in the conclusions.Comment: Extended version of the preprint submitted at ACM Computing Surveys (CSUR

Leveraging Kubernetes in Edge-Native Cable Access Convergence

Public clouds provide infrastructure services and deployment frameworks for modern cloud-native applications. As the cloud-native paradigm has matured, containerization, orchestration and Kubernetes have become its fundamental building blocks. For the next step of cloud-native, an interest to extend it to the edge computing is emerging. Primary reasons for this are low-latency use cases and the desire to have uniformity in cloud-edge continuum. Cable access networks as specialized type of edge networks are not exception here. As the cable industry transitions to distributed architectures and plans the next steps to virtualize its on-premise network functions, there are opportunities to achieve synergy advantages from convergence of access technologies and services. Distributed cable networks deploy resource-constrained devices like RPDs and RMDs deep in the edge networks. These devices can be redesigned to support more than one access technology and to provide computing services for other edge tenants with MEC-like architectures. Both of these cases benefit from virtualization. It is here where cable access convergence and cloud-native transition to edge-native intersect. However, adapting cloud-native in the edge presents a challenge, since cloud-native container runtimes and native Kubernetes are not optimal solutions in diverse edge environments. Therefore, this thesis takes as its goal to describe current landscape of lightweight cloud-native runtimes and tools targeting the edge. While edge-native as a concept is taking its first steps, tools like KubeEdge, K3s and Virtual Kubelet can be seen as the most mature reference projects for edge-compatible solution types. Furthermore, as the container runtimes are not yet fully edge-ready, WebAssembly seems like a promising alternative runtime for lightweight, portable and secure Kubernetes compatible workloads

Edge and Big Data technologies for Industry 4.0 to create an integrated pre-sale and after-sale environment

The fourth industrial revolution, also known as Industry 4.0, has rapidly gained traction in businesses across Europe and the world, becoming a central theme in small, medium, and large enterprises alike. This new paradigm shifts the focus from locally-based and barely automated firms to a globally interconnected industrial sector, stimulating economic growth and productivity, and supporting the upskilling and reskilling of employees. However, despite the maturity and scalability of information and cloud technologies, the support systems already present in the machine field are often outdated and lack the necessary security, access control, and advanced communication capabilities. This dissertation proposes architectures and technologies designed to bridge the gap between Operational and Information Technology, in a manner that is non-disruptive, efficient, and scalable. The proposal presents cloud-enabled data-gathering architectures that make use of the newest IT and networking technologies to achieve the desired quality of service and non-functional properties. By harnessing industrial and business data, processes can be optimized even before product sale, while the integrated environment enhances data exchange for post-sale support. The architectures have been tested and have shown encouraging performance results, providing a promising solution for companies looking to embrace Industry 4.0, enhance their operational capabilities, and prepare themselves for the upcoming fifth human-centric revolution