Beyond 5G URLLC Evolution: New Service Modes and Practical Considerations

Ultra-reliable low latency communications (URLLC) arose to serve industrial IoT (IIoT) use cases within the 5G. Currently, it has inherent limitations to support future services. Based on state-of-the-art research and practical deployment experience, in this article, we introduce and advocate for three variants: broadband, scalable and extreme URLLC. We discuss use cases and key performance indicators and identify technology enablers for the new service modes. We bring practical considerations from the IIoT testbed and provide an outlook toward some new research directions.Comment: Submitted to IEEE Wireless Commun. Ma

Networking Architecture and Key Technologies for Human Digital Twin in Personalized Healthcare: A Comprehensive Survey

Digital twin (DT), refers to a promising technique to digitally and accurately represent actual physical entities. One typical advantage of DT is that it can be used to not only virtually replicate a system's detailed operations but also analyze the current condition, predict future behaviour, and refine the control optimization. Although DT has been widely implemented in various fields, such as smart manufacturing and transportation, its conventional paradigm is limited to embody non-living entities, e.g., robots and vehicles. When adopted in human-centric systems, a novel concept, called human digital twin (HDT) has thus been proposed. Particularly, HDT allows in silico representation of individual human body with the ability to dynamically reflect molecular status, physiological status, emotional and psychological status, as well as lifestyle evolutions. These prompt the expected application of HDT in personalized healthcare (PH), which can facilitate remote monitoring, diagnosis, prescription, surgery and rehabilitation. However, despite the large potential, HDT faces substantial research challenges in different aspects, and becomes an increasingly popular topic recently. In this survey, with a specific focus on the networking architecture and key technologies for HDT in PH applications, we first discuss the differences between HDT and conventional DTs, followed by the universal framework and essential functions of HDT. We then analyze its design requirements and challenges in PH applications. After that, we provide an overview of the networking architecture of HDT, including data acquisition layer, data communication layer, computation layer, data management layer and data analysis and decision making layer. Besides reviewing the key technologies for implementing such networking architecture in detail, we conclude this survey by presenting future research directions of HDT

Remote Phobia Treatment as a Tactile Internet Application Case Study in Edge augmented with Mobile Ad Hoc Clouds Environment

Tactile Internet is a next generation Internet that allows the transmission of haptic sensations in addition to audio and video content. It is expected to enable new latency-sensitive and critical use cases, such as remote phobia treatment, tele-surgery and autonomous driving. However, the current networking infrastructure cannot ensure the strict requirements that come with Tactile Internet, namely ultra-responsiveness and ultra-reliability. \indent Edge computing can help in solving this issue. While Cloud Computing offers powerful computing resources at distant data centers, Edge computing provides resources closer to the end user. To this end, computations can be offloaded from the cloud to the edge to obtain lower latency. In addition, as the Edge itself may prove to be insufficiently close to the end users’ devices in some cases, it can be augmented with Mobile Ad-Hoc Clouds. The Mobile Ad-hoc Clouds refer to a group of mobile devices located at the immediate vicinity of the end users, offering their available resources for computation, leading therefore to a reduced latency. Nevertheless, the design and implementation of an architecture based on edges augmented with mobile ad-hoc clouds for Tactile Internet raises several challenges. Firstly, a tactile internet-based architecture for remote phobia treatment should allow the exchange of auditory, visual and haptic information to ensure the efficiency of the therapy. Secondly, the end to end latency should be in the order of a few milliseconds to avoid “cyber-sickness”. \indent This thesis provides a case study of edge augmented with mobile ad-hoc clouds architecture for remote phobia treatment. The contributions are threefold. First, a software architecture for remote phobia treatment is designed for an edge augmented with mobile ad hoc clouds environment. Second, a proof of concept prototype for the proposed architecture is implemented and evaluated using a set of haptic devices, which include the HTC Vive VR headset, the Leap Motion hand tracking device, as well as the Gloveone haptic glove. Third, a set of experiments consisting of placing the components in the different layers (i.e. Cloud, Edge and Mobile Ad-hoc Cloud) were conducted, which allowed an evaluation of the impact on performance. A set of high-level interfaces were introduced to allow communication with the heterogeneous devices. The design of the architecture as a set of software modules allows the reusability of the architecture

TSN-FlexTest: Flexible TSN Measurement Testbed (Extended Version)

Robust, reliable, and deterministic networks are essential for a variety of applications. In order to provide guaranteed communication network services, Time-Sensitive Networking (TSN) unites a set of standards for time-synchronization, flow control, enhanced reliability, and management. We design the TSN-FlexTest testbed with generic commodity hardware and open-source software components to enable flexible TSN measurements. We have conducted extensive measurements to validate the TSN-FlexTest testbed and to examine TSN characteristics. The measurements provide insights into the effects of TSN configurations, such as increasing the number of synchronization messages for the Precision Time Protocol, indicating that a measurement accuracy of 15 ns can be achieved. The TSN measurements included extensive evaluations of the Time-aware Shaper (TAS) for sets of Tactile Internet (TI) packet traffic streams. The measurements elucidate the effects of different scheduling and shaping approaches, while revealing the need for pervasive network control that synchronizes the sending nodes with the network switches. We present the first measurements of distributed TAS with synchronized senders on a commodity hardware testbed, demonstrating the same Quality-of-Service as with dedicated wires for high-priority TI streams despite a 200% over-saturation cross traffic load. The testbed is provided as an open-source project to facilitate future TSN research.Comment: 30 pages, 18 figures, 6 tables, IEEE TNSM, in print, 2024. Shorter version in print in IEEE Trans. on Network and Service Management (see related DOI below

A Cognitive Routing framework for Self-Organised Knowledge Defined Networks

This study investigates the applicability of machine learning methods to the routing protocols for achieving rapid convergence in self-organized knowledge-defined networks. The research explores the constituents of the Self-Organized Networking (SON) paradigm for 5G and beyond, aiming to design a routing protocol that complies with the SON requirements. Further, it also exploits a contemporary discipline called Knowledge-Defined Networking (KDN) to extend the routing capability by calculating the “Most Reliable” path than the shortest one. The research identifies the potential key areas and possible techniques to meet the objectives by surveying the state-of-the-art of the relevant fields, such as QoS aware routing, Hybrid SDN architectures, intelligent routing models, and service migration techniques. The design phase focuses primarily on the mathematical modelling of the routing problem and approaches the solution by optimizing at the structural level. The work contributes Stochastic Temporal Edge Normalization (STEN) technique which fuses link and node utilization for cost calculation; MRoute, a hybrid routing algorithm for SDN that leverages STEN to provide constant-time convergence; Most Reliable Route First (MRRF) that uses a Recurrent Neural Network (RNN) to approximate route-reliability as the metric of MRRF. Additionally, the research outcomes include a cross-platform SDN Integration framework (SDN-SIM) and a secure migration technique for containerized services in a Multi-access Edge Computing environment using Distributed Ledger Technology. The research work now eyes the development of 6G standards and its compliance with Industry-5.0 for enhancing the abilities of the present outcomes in the light of Deep Reinforcement Learning and Quantum Computing