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Intent-Based E2E Network Slice Management for Industry 4.0
... An E2E network slice comprises distinct subslices at the radio access network, transport network, and core network levels, all of which must be coordinated to meet the network slice E2E QoS requirements. Nevertheless, NS' shape, operation, relationship, and management constitute a thoughtprovoking issue that needs realistic intelligent methods to be established [111][112]. Consequently, the utilization of native AI is a necessity to optimize instantaneous wireless resource utilization between diverse slices due to their QoS requirements. ...
p>Smart services based on the Internet of Things (IoT) are likely to grow in popularity in the forthcoming years, necessitating the improvement of fifth-generation (5G) cellular networks upgrade of future networks from their present state. Despite the fact that the 5G cellular networks may manage a diversity of IoT services, they may not be able to fully meet the requirements of emerging smart applications due to their limitations that, in many cases, could be overcome by applying artificial intelligence (AI). Therefore, sixth–generation (6G) wireless technologies are being developed to address the limitations of 5G networks. Traditional machine learning (ML) techniques are driven in a centralized way. However, the huge volume of produced wireless data, the confidentiality concerns, and the growing computing competencies of wireless edge devices have led to the exposure of a promising solution in a decentralized way which is called distributed learning. This paper provides a comprehensive analysis of distributed learning (e.g., federated learning (FL), multi–agent reinforcement learning (MARL)–based FL framework) and how to deploy in an effective and efficient way for wireless networks. Moreover, we describe a timely comprehensive review of the role of FL in facilitating 6G enabling technologies, such as mobile edge computing, network slicing, satellite communications, terahertz links, blockchain, and semantic communications. Also, we identify and discuss several open research issues related to FL–empowered 6G wireless networks. In particular, we focus on FL for enabling an extensive range of smart services and applications. For each application, the main motivation for using FL along with the associated challenges and detailed examples for use scenarios are given. Regarding the AI techniques, we consider MARL–based FL framework tailored to the needs of future wireless networks for ensuring fast convergence and high model accuracy of large state and action spaces. Particularly, to manage the fast varying radio channels and limited radio resources (e.g., transmission power and radio spectrum) in a cellular communication environment, this article proposes a robust MARL–based FL framework to enable local users to perform distributed power allocation, mode selection, resource allocation, and interference management. Finally, the paper outlines several prospective upcoming research topics, aimed to create constructive incorporation of MARL–based FL framework for future wireless networks.</p
... Commonly, most wireless networks systems assume that the nature of the propagation radio channel characteristics is static. Following generations of wireless networks consider that channels are uncontrollable factors (Chirivella-Perez et al., 2021). MetaWireless will treat the environment as a quantity to enhance and optimize the network performance. ...
Fifth-generation (5G) mobile communication technology is now widely available in several countries, with millions of 5G customers. Therefore, it's time for academia and business to focus on the next generation. This paper will overview the sixth-generation (6G) mobile network, including motivations, use case scenarios, requirements, supported research projects, and technologies. We discuss the Beyond 5G (B5G) evolution and advanced 5G features to predict the critical 6G requirements and highlight the 6G capabilities. We also introduce the 6G scenarios, requirements, and technological components compared to 5G.
Moreover, the current status of 6G research is discussed, and a rough roadmap for specification and regulation is explored. Then we descrribe a few prospective applications, their benefits, concepts, and research directions. We explore the business direction for 6G by introducing the most recently 6G projects in the vertical markets. We also propose network architectural vision and the evolution of hardware-software designs to satisfy the higher requirements of 6G applications. This paper also presents a comprehensive survey for existing 6G trends, technologies, applications, industrial markets, and network structures for the most promising 6G applications.
The diverging requirements from various vertical industries have driven the paradigm shift in the next‐generation (5G) mobile networks, where network slicing has emerged as a major paradigm for this purpose by sharing and isolating resources over the same 5G physical infrastructure. To truly fulfill the different quality‐of‐service (QoS) requirements imposed by different network slices for different vertical applications, it is essential to introduce a programmable data plane that is aware of QoS and is configurable to enforce the QoS commitments. In this paper, we focus on designing, prototyping, and evaluating a novel QoS‐aware data‐plane network slicing framework for the edge and core network segments of a 5G network. The proposed framework is capable of dealing with differentiated services through hardware‐based traffic classification, priority configuration, and traffic scheduling. By leveraging the latest open‐source field‐programmable gate array platform, we prototype the proposed framework and empirically evaluate the performance of the prototyped system. Experiment results demonstrate the capabilities of the proposed framework in terms of achieving QoS‐aware network slicing at the data plane. • 5G hardware‐based network slicing for mobile edge computing architectures • Novel queuing architecture to implement 5G network slicing • Empirical demonstration implemented in hardware
Internet of Things (IoT) is a key business driver for the upcoming fifth-generation (5G) mobile networks, which in turn will enable numerous innovative IoT applications such as smart city, mobile health, and other massive IoT use cases being defined in 5G standards. To truly unlock the hidden value of such mission-critical IoT applications in a large scale in the 5G era, advanced self-protection capabilities are entailed in 5G-based Narrowband IoT (NB-IoT) networks to efficiently fight off cyber-attacks such as widespread Distributed Denial of Service (DDoS) attacks. However, insufficient research has been conducted in this crucial area, in particular, few if any solutions are capable of dealing with the multiple encapsulated 5G traffic for IoT security management. This paper proposes and prototypes a new security framework to achieve the highly desirable self-organizing networking capabilities to secure virtualized, multitenant 5G-based IoT traffic through an autonomic control loop featured with efficient 5G-aware traffic filtering. Empirical results have validated the design and implementation and demonstrated the efficiency of the proposed system, which is capable of processing thousands of 5G-aware traffic filtering rules and thus enables timely protection against large-scale attacks.
The progress in realizing the Fifth Generation (5G) mobile networks has been accelerated recently towards deploying 5G prototypes with increasing scale. One of the Key Performance Indicators (KPIs) in 5G deployments is the service deployment time, which should be substantially reduced from the current 90 hours to the target 90 minutes on average as defined by the 5G Public-Private Partnership (5G-PPP). To achieve this challenging KPI, highly automated and coordinated operations are required for the 5G network management. This paper addresses this challenge by designing and prototyping a novel 5G service deployment orchestration architecture that is capable of automating and coordinating a series of complicated operations across physical infrastructure, virtual infrastructure, and service layers over a distributed mobile edge computing paradigm, in an integrated manner. Empirical results demonstrate the superior performance achieved, which meets the 5G-PPP KPI even in the most challenging scenario where 5G services are installed from bare metal.
Software Defined Networking (SDN) focuses on the separation of data and control plane, while network function virtualization (NFV) decouples network functions from underlying hardware. Combining SDN with NFV would have many benefits, but the problem is how to integrate them. There are two possible architectures for such integration: the controller interacts with virtualized network functions (VNFs), or the switch interacts with VNFs. In this paper, the former is referred to as NFV under the controller (NFV_C) while the latter is called NFV aside the controller (NFV_AC). To the best of our knowledge, there is no analytical model for mathematically investigating the performance of such architectures. This paper therefore reports on the analytical modeling of SDN with NFV under or aside the controller. We model and analyze these two SDN + NFV architectures using an M/M/1 queuing model and validate our analysis with various simulations. We show that the analytical results match the simulation results very well. Furthermore, a packet delay reduction of 68.83% can be achieved for NFV_AC over NFV_C, meaning that NFV_AC is a better architecture for integrating SDN with NFV. We also consider feedback from the VNF to the switch. For low loads there is delay increase of 35.42% for high feedback (90%) in comparison with low feedback (10%). In the case of high loads we recorded a delay increase of 66.64%.
The grand objective of 5G wireless technology is to support services with vastly heterogeneous requirements. Network slicing, in which each service operates within an exclusive slice of allocated resources, is seen as a way to cope with this heterogeneity. However, the shared nature of the wireless channel allows non-orthogonal slicing, where services us overlapping slices of resources at the cost of interference. This paper investigates the performance of orthogonal and non-orthogonal slicing of radio resources for the provisioning of the three generic services of 5G: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable low-latency communications (URLLC). We consider uplink communications from a set of eMBB, mMTC and URLLC devices to a common base station. A communication-theoretic model is proposed that accounts for the heterogeneous requirements and characteristics of the three services. For non-orthogonal slicing, different decoding architectures are considered, such as puncturing and successive interference cancellation. The concept of reliability diversity is introduced here as a design principle that takes advantage of the vastly different reliability requirements across the services. This study reveals that non-orthogonal slicing can lead, in some regimes, to significant gains in terms of performance trade-offs among the three generic services compared to orthogonal slicing.
Manufacturing has evolved over the course of centuries from the days of handmade goods to the adoption of water- and steam-powered machines, the invention of mass production, the introduction of electronic automation, and now beyond. Today, the benchmark for companies to keep up with, is Industry 4.0. Here, Manufacturing systems go beyond simple connection, to also communicate, analyse and use collected information to drive further intelligent actions. It represents an integration of IoT, analytics, additive manufacturing, robotics, artificial intelligence, advanced materials, and augmented reality. The paper looks at the evolution of the Industrial revolution and the technologies that have impacted their growth. The proposed features of 5G technologies are listed and described how these features impact the Industries of the future, leading to Industries 4.0. 5G promises to be a key enabler for Factories of the Future, providing unified communication platform needed to disrupt with new business models and to overcome the shortcomings of current communication technologies.
The ever-increasing traffic demand is pushing network operators to find new cost-efficient solutions towards the deployment of future 5G mobile networks. The network sharing paradigm was explored in the past and partially deployed. Nowadays, advanced mobile network multi-tenancy approaches are increasingly gaining momentum paving the way towards further decreasing Capital Expenditures and Operational Expenditures (CAPEX/OPEX) costs, while enabling new business opportunities. This paper provides an overview of the 3GPP standard evolution from network sharing principles, mechanisms and architectures to future on-demand multi-tenant systems. In particular, it introduces the concept of the 5G Network Slice Broker in 5G systems, which enables mobile virtual network operators, over-the-top providers and industry vertical market players to request and lease resources from infrastructure providers dynamically via signaling means. Finally, it reviews the latest standardization efforts considering remaining open issues for enabling advanced network slicing solutions taking into account the allocation of virtualized network functions based on ETSI NFV, the introduction of shared network functions and flexible service chaining.
This paper presents and discuses the underlying infrastructure deployment of a cloud architecture used in our Data Center. This is based on a hybrid Virtual-Physical deployment for the cloud management platform OpenStack, where some of its principal management nodes of the cloud have been virtualized on a physical node. This particular infrastructure deployment opens the cloud to a wide number of new service possibilities with a lower complexity and cost time implementation. In the paper, we show as example of this extension a particular service that allows to perform real time network traffic analysis in the infrastructure.
Currently, network traffic monitoring tools do not fit well in the monitoring of cloud computing infrastructures. These tools are not integrated with the control plane of the cloud computing stack. This lack of integration causes a deficiency in the handling of the re-usage of IP addresses along virtual machines, a lack of adaption and reaction on highly frequent topology changes, and a lack of accuracy in the metrics gathered for the networking traffic flowing along the cloud infrastructure. The main contribution of this paper is to provide a novel SDN-based architecture to carry out the monitoring of network traffic in cloud infrastructures. The architecture in based on the integration between the SDN controller and the control plane of the cloud computing stack. The proposed architecture has been implemented using reference implementations such as OpenStack cloud infrastructures and FloodLight SDN controllers. A number of experiments have been executed in the prototype to validate the suitability and performance of the proposed architecture.
https://www.comsoc.org/publications/ctn/5g-can-shape-mission-critical-healthcare-services
Seamless connectivity for patients, first responders and health care professionals including medical centres is becoming an important aspect of the quality of emergency medical care. 5G networks and related technologies can significantly improve “care on the go”, assisting first responders and health care service providers by enabling guaranteed wireless connectivity and real time multimedia communications with hospitals in advance of patient arrival. In this article, Ignacio, Jose, Qi, Gelayol, Enrique and Pablo consider the use of network slicing as one of the key elements enabling high quality real time multimedia communication between emergency medical personnel and hospitals. They present a network slicing architecture, and its implementation, as part of their 5G trials for the European project SliceNet, and discuss technical requirements for real time video or information transmission. They also argue that such shared but highly reliable connectivity could make ambulances more intelligent, further enabling emerging tools such as machine learning or artificial intelligence to further improve real time services.
Network slicing is a primary Fifth-Generation (5G) mobile networking technology to create virtualised and softwarised logical networks for various vertical businesses with diverging Quality of Service (QoS) requirements. Meanwhile, there is a clear gap in providing network slicing capabilities in 5G multi-tenant networks to enable guaranteed QoS in terms of well-defined network metrics for the multiple tenants sharing the same physical infrastructure. This paper designs and implements novel software data path architecture that enables such network slicing with assured QoS in 5G multi-tenant networks. Highly flexible and customisable definition of network slicing is also allowed to be aligned with different existing definitions on demand and at run time. The proposed architecture has been prototyped based on the popular Open Virtual Switch (OVS), and empirically validated to demonstrate the deployment and management of network slices with the above capabilities. Intensive scalability results are provided where more than 8,192 network slices are achieved simultaneously with warranted QoS through performance isolation in terms of bandwidth and delay in a real softwarised 5G multi-tenant infrastructure at speeds of up to 10 Gbps.
The Fifth-Generation (5G) mobile networks leverage virtualisation and softwarisation to reduce both capital and operating expenditures whilst benefiting from network programmability and flexibility for various use cases. Meanwhile, virtualisation and softwarisation introduce unprecedented complexity to network infrastructure topologies, which poses substantial challenges to network topology management. This paper proposes a novel architecture to enable network administrators to achieve real-time network discovery and spatial representation of the software data path, containers, virtual machines, and geographically distributed edges to help network troubleshooting and management tasks. Another important innovation is the flexibility to support a significant number of business roles by means of a novel method to perform data model alignment between different business roles. The architecture has been designed, prototyped and validated, and experiment results have demonstrated promising scalability of the proposed solution.
The increasing popularity of video applications and ever-growing high-quality video transmissions (e.g. 4K resolutions), has encouraged other sectors to explore the growth of opportunities. In the case of health sector, mobile Health services are becoming increasingly relevant in real-time emergency video communication scenarios where a remote medical experts’ support is paramount to a successful and early disease diagnosis. To minimize the negative effects that could affect critical services in a heavily loaded network, it is essential for 5G video providers to deploy highly scalable and priorizable in-network video optimization schemes to meet the expectations of a large quantity of video treatments. This paper presents a novel 5G Video Optimizer Virtual Network Function () that leverages the latest technologies in 5G and video processing to address this important challenge. Advanced traffic filtering is coupled with Scalable H.265 video coding to enable run-time bandwidth-saving video optimization without compromising Quality of Service (QoS); kernel-space video processing is introduced to achieve further performance gains; and the use of a Virtual Network Function (VNF) facilitates dynamic deployment of virtualized video optimizers to achieve scalability and flexibility in this service. The proposed approach is implemented in a realistic 5G testbed and empirical results demonstrate the superior scalability and performance achieved.
This paper presents the design and prototype implementation of the SELFNET fifth‐generation (5G) mobile edge infrastructure. In line with the current and emerging 5G architectural principles, visions, and standards, the proposed infrastructure is established primarily based on a mobile edge computing paradigm. It leverages cloud computing, software‐defined networking, and network function virtualization as core enabling technologies. Several technical solutions and options have been analyzed. As a result, a novel portable 5G infrastructure testbed has been prototyped to enable the preliminary testing of the integrated key technologies and to provide a realistic execution platform for further investigating and evaluating software‐defined networking– and network function virtualization–based application scenarios in 5G networks.
The Fifth-Generation (5G) networks, as the emerging next generation mobile networks, are adopting softwarization and virtualization technologies as the cornerstones for the network operators to gain significant competitive advantages by reducing both capital and operational expenditure, enabling agile and flexible service creation and deployment, among others. Meanwhile, a virtualized and softwarized 5G network would suffer from downgraded system performance due to this unprecedented paradigm shift towards software-based networking. Addressing one of the top challenges in this context, this paper focuses on improving the performance of the data plane from the edge to the core network segment (backhaul) in a 5G multi-tenant network by leveraging and exploring the programmability introduced by software-based networking. A fully functional prototype has been designed and implemented utilizing a Field Programmable Gate Arrays (FPGAs) acceleration-based platform, and the prototyped system has been empirically tested and evaluated to demonstrate the superior performance enhancements. The proposed solution can effectively support 5G networks in delivering mission-critical or time-sensitive applications such as ultra-high definition video use cases as experimentally validated and shown in this paper, by fulfilling the strict Quality of Service (QoS) requirements imposed to the data plane.
Although the radio access network (RAN) part of mobile networks offers a significant opportunity for benefiting from the use of SDN ideas, this opportunity is largely untapped due to the lack of a software-defined RAN (SD-RAN) platform. We fill this void with FlexRAN, a flexible and programmable SD-RAN platform that separates the RAN control and data planes through a new, custom-tailored southbound API. Aided by virtualized control functions and control delegation features, FlexRAN provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. We implement FlexRAN as an extension to a modified version of the OpenAirInterface LTE platform, with evaluation results indicating the feasibility of using FlexRAN under the stringent time constraints posed by the RAN. To demonstrate the effectiveness of FlexRAN as an SD-RAN platform and highlight its applicability for a diverse set of use cases, we present three network services deployed over FlexRAN focusing on interference management, mobile edge computing and RAN sharing.
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