The envisioned 6G networks are expected to support extremely high data rates, low-latency, and radically new applications empowered by machine learning. The futuristic 6G networks require a novel framework that can be used to operate, manage, and optimize its underlying services such as ultra-reliable and low-latency communication, and Internet of everything. In recent years, artificial intelligence (AI) has demonstrated significant success in optimizing and designing networks. The AI-enabled traffic orchestration can dynamically organize different network architectures and slices to provide quality of experience considering the dynamic nature of the wireless communication network.
In this paper, we propose a digital twin enabled network framework, empowered by AI to cater the variability and complexity of envisioned 6G networks, to provide smart resource management and intelligent service provisioning. Digital twin paves a way for achieving optimizing 6G services by creating a virtual representation of the 6G network along with its associated communication technologies (e.g., intelligent reflecting surfaces, terahertz and millimeter communication), computing systems (e.g., cloud computing and fog computing) with its associated algorithms (e.g., optimization and machine learning). We then discuss and review the existing AI-enabled traffic management and orchestration techniques and highlight future research directions and potential solutions in 6G networks.
Heterogeneous quantum key distribution chain orchestration over optical networks is demonstrated with software-defined networking (SDN), achieving the control-layer interoperability for BB84 (Bennett-Brassard-1984) and TF (Twin-Field) based quantum key distribution devices.
Dynamic and flexible optical networking enabled by NFV and SDN are the key technology enablers for supporting the dynamicity and bandwidth requirements of emerging 5G network services. To achieve the objective of 5G, Network Services (NSes) must be often deployed transparently over multiple administrative and technological domains. Such case often presents security risks since a typical NS may comprise a chain of network functions, each executed in different remote locations, and tampering within the network infrastructure may compromise their communication. To avoid such threats, QKD has been…
Accommodating digital twins (DTs) in the metaverse is essential to achieving digital reality. This need for integrating DTs into the metaverse while operating them at the network edge has increased the demand for a decentralized edge-enabled metaverse. Hence, to consolidate the fusion between real and digital entities, it is necessary to harmonize the interoperability between DTs and the metaverse at the edge. In this paper, a novel decentralized metaverse framework that incorporates DT operations at the wireless edge is presented. In particular, a system of autonomous physical twins (PTs) ope…
This article documents one of the world's first standards-compliant pre-commercial end-to-end 5th generation (5G) systems. Focus is on a standardized 5G architecture which includes the underlying 3GPP components but also the ETSI Network Function Virtualization (NFV) management and orchestration capabilities. The truly innovative character of 5G enabling fundamental changes to architecture and implementation is discussed, and details of monitoring and orchestration approaches that are deemed instrumental in unlocking the full potential of 5G. Finally, it is important to us to share the lessons…
This paper presents the vision of the Control Exchange Point (CXP) architectural model. The model is motivated by the inflexibility and ossification of today's inter-domain routing system, which renders critical QoS-constrained end-to-end (e2e) network services difficult or simply impossible to provide. CXPs operate on slices of ISP networks and are built on basic Software Defined Networking (SDN) principles, such as the clean decoupling of the routing control plane from the data plane and the consequent logical centralization of control. The main goal of the architectural model is to provide …
Network slicing (NS) and multi-access edge computing (MEC) are new paradigms which play key roles in 5G and beyond networks. NS allows network operators (NOs) to divide the available network resources into multiple logical NSs for providing dedicated virtual networks tailored to the specific service/business requirements. MEC enables NOs to provide diverse ultra-low latency services for supporting the needs of different industry verticals by moving computing facilities to the network edge. NS can be constructed by instantiating a set of virtual network functions (VNFs) on top of MEC cloud serv…
Artificial intelligence (AI)-driven zero-touch network slicing (NS) is a new paradigm enabling the automation of resource management and orchestration (MANO) in multi-tenant beyond 5G (B5G) networks. In this paper, we tackle the problem of cloud-RAN (C-RAN) joint slice admission control and resource allocation by first formulating it as a Markov decision process (MDP). We then invoke an advanced continuous deep reinforcement learning (DRL) method called twin delayed deep deterministic policy gradient (TD3) to solve it. In this intent, we introduce a multi-objective approach to make the central…
In existing wireless networks, the control programs have been designed manually and for certain predefined scenarios. This process is complicated and error-prone, and the resulting control programs are not resilient to disruptive changes. Data-driven control based on Artificial Intelligence and Machine Learning (AI/ML) has been envisioned as a key technique to automate the modeling, optimization and control of complex wireless systems. However, existing AI/ML techniques rely on sufficient well-labeled data and may suffer from slow convergence and poor generalizability. In this article, focusin…
With the constant demand for connectivity at an all-time high, Network Service Providers (NSPs) are required to optimize their networks to cope with rising capital and operational expenditures required to meet the growing connectivity demand. A solution to this challenge was presented through Network Function Virtualization (NFV). As network complexity increases and futuristic networks take shape, NSPs are required to incorporate an increasing amount of operational efficiency into their NFV-enabled networks. One such technique is Machine Learning (ML), which has been applied to various entitie…
Adaptive Digital Twin and Communication-Efficient Federated Learning Network Slicing for 5G-enabled Internet of Things
School of Computer Science and Engineering, University of Electronic Science and Technology of China（电子科技大学计算机科学与工程学院）；School of Electro-optical Engineering, Chongqing University of Posts and Telecommunications（重庆邮电大学光电工程学院）；Technische University（工业大学）
Emerging technologies and applications make the network unprecedentedly complex and heterogeneous, leading physical network practices to be costly and risky. The digital twin network (DTN) can ease these burdens by virtually enabling users to understand how performance changes accordingly with modifications. For this "What-if" performance evaluation, conventional simulation and analytical approaches are inefficient, inaccurate, and inflexible, and we argue that data-driven methods are most promising. In this article, we identify three requirements (fidelity, efficiency, and flexibility) for pe…
Modular Multi-Domain Digital Twin Architecture: Sustainable Intent-Driven 6G Management
University of Applied Sciences and Arts Western Switzerland（西部瑞士应用科学与艺术大学）；Technische Universität Berlin（柏林工业大学）；Poznań University of Technology（波兹南理工大学）；Centrum Wiskunde & Informatica（荷兰数学与计算机科学研究中心）；Eindhoven University of Technology（埃因霍温理工大学）；Centre Tecnològic de Telecomunicacions de Catalunya（加泰罗尼亚电信技术中心）；Telefónica Innovación Digital（西班牙电信数字创新）；Ceragon Networks（萨瑞昂网络）
Space-air-ground integrated network (SAGIN) is considered as a core requirement in emerging 6G networks, which integrates the terrestrial and non-terrestrial networks to reach the full network coverage and ubiquitous services. To envision the ubiquitous intelligence and the deep integration in 6G SAGIN, a paradigm of cybertwin-enabled 6G SAGIN is presented in this paper. Specifically, a cybertwin-enabled SAGIN architecture is first presented, where a novel five-dimension digital twin (DT) model is presented. Particularly, three categories of critical technologies are presented based on the cyb…
Management and orchestration (MANO) of resources by virtual network functions (VNFs) represents one of the key challenges towards a fully virtualized network architecture as envisaged by 5G standards. Current threshold-based policies inefficiently over-provision network resources and under-utilize available hardware, incurring high cost for network operators, and consequently, the users. In this work, we present a MANO algorithm for VNFs allowing a central unit (CU) to learn to autonomously re-configure resources (processing power and storage), deploy new VNF instances, or offload them to the …
Digital Twinning of a Pressurized Water Reactor Startup Operation and Partial Computational Offloading in In-network Computing-Assisted Multiaccess Edge Computing
Chonnam National University（全南大学）；Institute for Energy Technology（能源技术研究所）
A 5G network provides several service types, tailored to specific needs such as high bandwidth or low latency. On top of these communication services, verticals are enabled to deploy their own vertical services. These vertical service instances compete for the resources of the underlying common infrastructure. We present a resource arbitration approach that allows to handle such resource conflicts on a high level and to provide guidance to lowerlevel orchestration components.
The Internet of Things (IoT) is advancing and the adoption of internet-connected devices in everyday use is constantly growing. This increase not only affects the traffic from other sources in the network, but also the communication quality requirements, like Quality of Service (QoS), for the IoT devices and applications. With the rise of dynamic network management and dynamic network programming technologies like Software-Defined Networking (SDN), traffic management and communication quality requirements can be tailored to fit niche use cases and characteristics. We propose a publish/subscrib…
AI-driven Orchestration at Scale: Estimating Service Metrics on National-Wide Testbeds
Federal University of Viçosa (UFV)（佛罗里达大学维索萨分校）；Federal University of Uberlândia (UFU)（联邦乌贝利亚大学）；Salvador University (UNIFACS)（萨尔瓦多大学）；University of São Paulo (USP)（圣保罗大学）；University of Minho (UMinho)（明霍大学）
Optimizing Reinforcement Learning Training over Digital Twin Enabled Multi-fidelity Networks
Department of Electrical and Computer Engineering, University of Miami（电子与计算机工程系，迈阿密大学）；Ericsson Research（爱立信研究）；European AI Office, European Commission（欧洲人工智能办公室，欧盟委员会）
