The fifth-generation mobile evolution introduces Next-Generation Radio Access Networks (NG-RAN), splitting the RAN protocol stack into the eight disaggregated options combined into three network units, i.e., Central, Distributed, and Radio. The disaggregated units reach full interoperability on Open RAN. Further advances allow the RAN software to be virtualized (vNG-RAN) on top of general-purpose hardware, enabling the management of disaggregated units and protocols as radio functions. The placement of these functions is challenging since the best decision must be based on multiple constraints, e.g., the RAN protocol stack split, routing paths in network topologies with restricted bandwidth and latency, asymmetric computational resources, etc. The literature does not deal with general placement problems with high functional split options and protocol stack analysis. This article proposes the first exact model for positioning radio functions for vNG-RAN planning, named PlaceRAN, as a Binary Integer Linear Programming (BILP) problem. The objective is to minimize the computing resources and maximize the aggregation of radio functions. The evaluation considered two realistic network topologies, and the results reveal that PlaceRAN achieves an optimized high-performance aggregation level. It is flexible for RAN deployment overcoming the network restrictions, and up to date with the most advanced vNG-RAN design and development.

Network slicing is a powerful paradigm for network operators to support use cases with widely diverse requirements atop a common infrastructure. As 5G standards are completed, and commercial solutions mature, operators need to start thinking about how to integrate network slicing capabilities in their assets, so that customer-facing solutions can be made available in their portfolio. This integration is, however, not an easy task, due to the heterogeneity of assets that typically exist in carrier networks. In this regard, 5G commercial networks may consist of a number of domains, each with a different technological pace, and built out of products from multiple vendors, including legacy network devices and functions. These multi-technology, multi-vendor and brownfield features constitute a challenge for the operator, which is required to deploy and operate slices across all these domains in order to satisfy the end-to-end nature of the services hosted by these slices. In this context, the only realistic option for operators is to introduce slicing capabilities progressively, following a phased approach in their roll-out. The purpose of this paper is to precisely help designing this kind of plan, by means of a technology radar. The radar identifies a set of solutions enabling network slicing on the individual domains, and classifies these solutions into four rings, each corresponding to a different timeline: (i) as-is ring, covering today’s slicing solutions; (ii) deploy ring, corresponding to solutions available in the short term; (iii) test ring, considering medium-term solutions; and (iv) explore ring, with solutions expected in the long run. This classification is done based on the technical availability of the solutions, together with the foreseen market demands. The value of this radar lies in its ability to provide a complete view of the slicing landscape with one single snapshot, by linking solutions to information that operators may use for decision making in their individual go-to-market strategies.

This perspective paper introduces a novel framework for container orchestration called CODECO. The CODECO orchestration framework relies on a data-network-computing approach to define the best infrastructure that can support the operation of next-generation Internet applications across a mobile, heterogeneous Edge-Cloud continuum. The selection of such an infrastructure is aligned with target performance profiles defined by the user, such as resilience or greenness. CODECO proposes to rely on decentralized Artificial Intelligence approaches in an attempt to provide the most suitable infrastructure to an application deployment, considering infrastructural challenges, such as intermittent connectivity and node failure. This paper explains the current CODECO framework and provides insight into operational use-cases where CODECO is being deployed, as relevant examples of application for such a framework. Recent developments in the creation of the open-source CODECO framework are described and explained, allowing the use of the framework by the research community. The paper then provides a thorough analysis of CODECO’s features in comparison with existing orchestration frameworks, explaining the benefits introduced with this dynamic orchestration approach.

Service providers highly rely on network softwarization for addressing the demanding use cases of the 5G verticals. In order for the 5G vertical scenarios to be seamlessly executed, where the coverage should be provided in large areas, the required infrastructure capacity and availability can only be supported by cross-operator cooperation. In this context, we employ a novel federated core-edge 5G architecture, where 5G vertical services are represented as service function chains (SFCs) and can be offered on the infrastructure owned either by the local operator or a foreign one. Furthermore, we propose two online SFC placement methods that aim to efficiently place the SFCs across the architecture, taking into account the deployment cost. A simulation of the optimal solution, based on an integer linear programming (ILP) approach, is evaluated against a hop-based heuristic placement method that runs on our experimental 5G platform. Our experimental results demonstrate that the optimized placement produces the most cost-effective solution. Our heuristic algorithm introduces a near-optimal solution, but with a higher deployment cost. Compared with the ILP approach, the heuristic solution provides lower complexity and execution time. Finally, in order to further augment the placement techniques, we propose enhanced lifecycle management methods that use live migration and scaling actions to further decrease the execution cost and adapt to real-time incoming traffic, respectively.

Traditionally microwave backhaul has been configured and operated in a static manner by means of vendor specific management systems. This mode of operation will be difficult to adapt to the new challenges originated by 5G networks. New mechanisms for adaptation and flexibility are required also in this network segment. The usage of a signaled control plane solution (based on OpenFlow) will facilitate the operation and will provide means for automation of actions on the wireless transport network segment. In addition to that, a standard control plane helps to reach the multi-vendor approach reducing complexity and variety of current per-vendor operation. This paper presents the motivation for the introduction of programmability concepts in wireless transport networks and illustrate the applicability of such control plane with two relevant use cases for dynamically controlling wireless transport nodes in 5G networks. Extensions to OpenFlow protocol are also introduced for building Software Defined Wireless Transport Networks (SDWTNs).

The rapid evolution of 5G and beyond technologies has sparked an unprecedented surge in the need for networking infrastructure that can deliver high speed, minimal latency, and remarkable flexibility. The programmable data plane, which enables the dynamic reconfiguration of network functions and protocols, is becoming increasingly important in meeting these requirements. This paper provides an overview of the current state of the art in programmable data planes implemented in 5G and beyond architectures. It proposes a classification of the reviewed studies based on system architecture and specific use cases. Furthermore, the article surveys the primary applications of programmable devices in emerging telecommunication networks, such as tunneling and forwarding, network slicing, cybersecurity, and in-band telemetry. Finally, this publication summarizes the open research challenges and future directions. In addition to offering a comprehensive review of programmable data plane applications in telecommunication networks, this article aims to guide further research in this promising field for network operators and researchers alike.