5G Slices Research Articles

On the Impact of 5G Slicing on an Internet of Musical Things System

On the Impact of 5G Slicing on an Internet of Musical Things System

Performance of 5G Slicing with Access Technologies, and Diversity: A Review and Challenges

Performance of 5G Slicing with Access Technologies, and Diversity: A Review and Challenges

Crowd‐sourced and incentive driven UAV system to assist with network slices

AbstractOwing to their flexibility, fast deployment, increasing affordability, and numerous application opportunities, unmanned aerial vehicles (UAVs) became an undisputed target of studies and research to discover and exploit the immense opportunities they provide. Moreover, network slicing is a critical enabler for 5G and beyond. Network slices guarantee certain network user expectations such as data rate and latency thresh‐holds. There is no doubt that crowd‐sourced and incentive driven solutions are on the rise. Crowd‐sourcing allowed companies and organizations both small and large to gather data and perform other large‐scale tasks with minimum expenses and maintenance. Indeed, the major concerns for 5G and network slicing are guaranteeing high throughput, reliability, and latency. With data rates being the most important attribute for common regular users, that is, mobile devices, video streaming, navigation, and content consumption. As a result, the focus of this work is to utilize crowd‐sourced UAVs in an incentive driven network slice assistance system to extend coverage and provide mobile users with the high throughput they require. This work presents some basic 5G cellular radio access technologies and network slicing background and proposes a novel system, namely UAV slice assistance (UAVSA), and its hybrid alternative version: UAV hybrid slice assistance (UAVHSA). The hybrid mode combines benefits from the proposed UAVSA system and the traditional base station (BS) system. The proposed algorithms address the issue of coverage and guaranteeing high data rate slices for users. The proposed systems maximize satisfaction rate of network slice users. Moreover, all systems are extensively tested and compared in various scenarios to determine their performance and provide a coherent study. Finally, future works and opportunities are highlighted in conclusion.

Control coordination in inverter‐based microgrids using AoI‐based 5G schedulers

AbstractA coordinated set point automatic adjustment with correction enabled (C‐SPAACE) framework that uses 5G communication for real‐time control coordination between inverter‐based resources (IBR) in microgrids is proposed. Utilising slicing capability, 5G offers low‐latency communication to C‐SPAACE under normal conditions. However, given the multitude of power grid use cases, a certain 5G slice for C‐SPAACE may have access only to limited radio spectrum resources, which if not managed well, greatly undermines the communication needs of C‐SPAACE framework. Thus, optimally scheduling the available spectrum resources among IBRs in a sliced 5G network‐based C‐SPAACE framework becomes a critical problem. To address this issue, the authors utilise a novel age of information (AoI) metric and designs an AoI‐based 5G scheduler to provide low‐latency communication to C‐SPAACE. Following this, a co‐simulation environment is designed using PSCAD/EMTDC and Python to simulate a microgrid supported by 5G communication. Time‐domain simulation case studies are performed using the proposed co‐simulation environment to evaluate the performance of C‐SPAACE using 5G with both AoI‐based and other baseline (non‐AoI) schedulers.

Prioritizing protection communication in a 5G slice: Evaluating HTB traffic shaping and UL bitrate adaptation for enhanced reliability

Abstract5G network slicing is promising in prioritizing time‐critical protection communication in wireless networks of smart grids. However, network slicing offered by telecommunication providers encompasses all smart grid applications, lacking granularity. Smart grid automation standards provide recommendations on prioritization of protection communication to improve reliability but only for wired connections. Therefore, this paper investigates hierarchical token bucket (HTB) traffic shaping and uplink (UL) bitrate adaptation of a live video stream for prioritizing protection communication within a 5G slice. An experimental setup combines controller‐hardware‐in‐the‐loop (CHIL) with a quality of service (QoS) measurement system for validation. The system under test consists of commercial 5G networks, intelligent electronic devices (IEDs), and merging units for validation with three smart grid applications: fault location, line differential, and intertrip protection. HTB traffic shaping improves protected faults by 47.57% in congested and 1.16% in non‐congested scenarios. UL bitrate of the video stream adaptation by 2 Mbps increases protected faults by 3.69%. HTB traffic shaping even improves prioritization with a wired connection without introducing additional delays. HTB traffic shaping must be deployed in routers to maintain good QoS for critical applications. Collaboration between utilities and telecommunication providers is essential to effectively deploy 5G network slicing on smart grids.

Cooperative-Aware Radio Resource Allocation Scheme for 5G Network Slicing in Cloud Radio Access Networks.

The 5G network is designed to serve three main use cases: enhanced mobile broadband (eMBB), massive machine-type communications (mMTC), and ultra-reliable and low-latency communications (uRLLC). There are many new technological enablers, including the cloud radio access network (C-RAN) and network slicing, that can support 5G and meet its requirements. The C-RAN combines both network virtualization and based band unit (BBU) centralization. Using the network slicing concept, the C-RAN BBU pool can be virtually sliced into three different slices. 5G slices require a number of Quality of service (QoS) metrics, such as average response time and resource utilization. In order to enhance the C-RAN BBUs utilization while protecting the minimum QoS of the coexisting three slices, a priority-based resource allocation with queuing model is proposed. The uRLLC is given the highest priority, while eMBB has a higher priority than mMTC services. The proposed model allows the eMBB and mMTC to be queued and the interrupted mMTC to be restored in its queue to increase its chance to reattempt the service later. The proposed model's performance measures are defined and derived using a continuous-time Markov chain (CTMC) model and evaluated and compared using different methodologies. Based on the results, the proposed scheme can increase C-RAN resource utilization without degrading the QoS of the highest-priority uRLLC slice. Additionally, it can reduce the forced termination priority of the interrupted mMTC slice by allowing it to re-join its queue. Therefore, the comparison of the results shows that the proposed scheme outperforms the other states of the art in terms of improving the C-RAN utilization and enhancing the QoS of eMBB and mMTC slices without degrading the QoS of the highest priority use case.

Control–Communication–Computing Co-Design in Cyber–Physical Production System

The cyber–physical production system (CPPS) has practical requirements, such as distributed, reconfigurable, and high-performance, which bring a new challenge to performance guarantee of remote manufacturing with time delay under shared resources. Time delay has a great influence on system performance, and the mainstream methods mainly reduce its influence by optimizing control. However, due to the uncertainty of time delays, the existing methods have great limitations, and the configuration complexity is high. To address this issue, we take teleoperation as the control model, then we introduce 5G slicing and edge computing technologies to turn this control problem into a control–communication–computing co-design problem. An industrial teleoperation testbed is implemented to help clarify this problem and explore the key points in solving it. Then, a novel co-design teleoperation platform (CdTP) is designed that can quantitatively describe the relationship between the time delay and system configuration. Based on CdTP, system performance assurance does not have to be achieved by blindly increasing the total amount of resources, but can be achieved by improving the utilization of shared control–communication–computing resources. In addition, CdTP can dynamic configure resources based on changing requirements, which make it combines flexibility, real time, and reliability. Finally, we propose a resource allocation method to minimize the maximum job delay. The evaluation and experimental results indicate that our platform can achieve an all-in-one configuration, and validation of the proposed method is conducted to provide deterministic delay guarantees.

Mission Critical Communications Support With 5G and Network Slicing

Mission Critical (MC) communications take a pivotal role to achieve effective Public Protection and Disaster Relief (PPDR) actions. Even though 3GPP standards define MC applications and services in an architectural framework compatible with current 5G mobile networks, real-life experiments and applications of these concepts are still at the very beginning. In this paper, we present an architectural study and related experimental activity on network slicing for MC communications. We implemented these services in a fully virtualized environment, and deployed and tested them in a multi-domain network slicing scenario compliant with the ETSI NFV-MANO specifications. Our work aligns with the 5G approach separating control and data planes. The level of automation in service deployment and the slice isolation features are demonstrated, showing the benefits in terms of application performance, management flexibility, scalability, and quality of service differentiation capabilities.

Knowledge-based flexible resource allocation optimisation strategy for multi-tenant radio access network slicing in 5G and B5G

Formalisation of the network slice as a resource allocation unit is considered a promising aspect that enables scalable and flexible resource allocation among many tenants in 5G and beyond 5G (B5G) communication networks. However, the user traffic has to be passed through the central administration for processing, which leads to latency problems. To solve this problem, recent research works have suggested fixed central-to-edge resource allocation ratios as per the service type. However, this approach leads to over-provisioning of some resources. This paper provides a flexible resource allocation approach for 5G slice networks operating in a heterogeneous environment with multiple tenants and tiers. A radial basis-neural network is used to convert abstract specifications of simulation activities into precise resource needs, and then a genetic algorithm-based flexible multi-resource allocation scheme is proposed, where a versatile optimisation framework is used. The results show that the proposed approach outperforms such existing schemes.

Service Function Chains Deployment for 5G Slice With Bandwidth Coupling

Network function virtualization (NFV) technology is the key technology to solve the flexibility problem of 5G network. Multiple service function chains (SFCs) that coexist on physical infrastructure within a slice share the resources of the infrastructure. Therefore, how to allocate resources to an SFC under QoS constraints and further, how to build a resource sharing model among multiple SFCs are significant. In this letter, we jointly consider the above problems and propose a coupling bandwidth resource allocation model (CBRA) for the resource sharing of multiple SFCs. In this model, we define the effective coupling bandwidth increment(ECBI) based on the statistical feature of traffic and construct the homogeneous traffic flows on the infrastructure within the slice as the coupled traffic. Furthermore, based on the CBRA model, we establish an integer linear programming (ILP) problem aiming at minimizing resource occupancy to solve the SFCs deployment and realize the joint resource allocation of multiple SFCs. Simulation results show that the deployment algorithm can achieve QoS guarantee and effectively save bandwidth for homogeneous business.

Learning Long- and Short-Term Temporal Patterns for ML-Driven Fault Management in Optical Communication Networks

The deployment of 5G and network slicing has challenged the current network management requirements, triggering the need for programmable and software-driven architectures. Thus, automated real-time fault management for self-managed networks with machine learning and artificial intelligence at the forefront has become necessary. This is especially the case of optical communication systems, accountable for most of the data traffic worldwide. This study introduces the application of a novel failure detection and localization framework capable of forecasting failures in optical systems based on an unsupervised learning strategy. In this approach, the Long- and Short-term Time-series Network (LSTNet) is exploited for modeling the normal behavior of optical systems. Then, failure conditions are properly forecast without explicitly training the model for such cases, easing the data acquisition process. Later, forecast values and actual measurements from optical equipment are used to derive an outlier detection method to detect and locate failures to improve the decision-making process at the network orchestrator. Laboratory experiments comparing the proposed approach with the Recurrent and Long Short-Term Memory models in terms of failure detection and forecasting performance show that using the LSTNet reduces the mean squared errors in 95% for unseen data, indicating robustness and suitability for real-world environments.

SDN East–West cooperation in a converged fixed-mobile optical access network: enabling 5G slicing capabilities

The new 5G service requirements will force operators to rethink the deployment of infrastructure and management tools. The reuse of passive optical network (PON) technology to connect antenna sites has attracted the attention of some operators, as the high availability of some 5G services, as well as ubiquitous radio coverage in a denser network, could be ensured with minimum deployment efforts. In this case, the implications of each 5G slice instance deserve to be clarified in a PON infrastructure, and a fixed-mobile converged management system in optical access networks (ANs) will be necessary for operators. Some class of service (CoS) algorithms must be developed to ensure that different and heterogeneous services are properly transported through optical fibers in a fixed-mobile converged scenario. Many organizations are considering the use of transmission containers (T-CONTs) (the indicator of the bandwidth distribution in the PON uplink) for PON slicing, but the CoS for mobile traffic in a PON has not yet been defined. In parallel, the new AN management solutions are mostly focused on software-defined network (SDN) northbound/southbound interfaces between orchestrators and abstraction entities. However, if an end-to-end 5G slice instance must be dynamically applied in a fixed-mobile converged architecture, the coordination between mobile and residential management systems is necessary. We propose a disaggregated optical line terminal (OLT) with an SDN controller that leverages the advantages of virtualization technologies and the currently deployed OLT. We propose an East–West interface between fixed and mobile SDN controllers and have successfully implemented a 5G slicing proof of concept in access transport networks using this interface. We succeeded in reducing uplink latency and jitter by 25%–50% thanks to a smart optimization of T-CONTs, which could be interesting for ultrareliable and low-latency communications applications. A discussion of T-CONTs for slicing is also given based on experimental measurements.

Quality of Service based resource allocation in D2D enabled 5G-CNs with network slicing

With the rapid new advancements in technology, there is an enormous increase in devices and their versatile need for services. Fifth-generation (5G) cellular networks (5G-CNs) with network slicing (NS) have emerged as a necessity for future mobile communication. The available network is partitioned logically into multiple virtual networks to provide an enormous range of users’ specific services. Efficient resource allocation methods are critical to delivering the customers with their required Quality of Service (QoS) priorities. In this work, we have investigated a QoS based resource allocation (RA) scheme considering two types of 5G slices with different service requirements; (1) enhanced Mobile Broadband (eMBB) slice that requires a very high data rate and (2) massive Machine Type Communication (mMTC) slice that requires extremely low latency. We investigated the device-to-device (D2D) enabled 5G-CN model with NS to assign resources to users based on their QoS needs while considering the cellular and D2D user’s data rate requirements. We have proposed a Distributed Algorithm (DA) with edge computation to solve the optimization problem, which is novel as edge routers will solve the problem locally using the augmented Lagrange method. They then send this information to the central server to find the global optimum solution utilizing a consensus algorithm. Simulation analysis proves that this scheme is efficient as it assigns resources based on their QoS requirements. This scheme is excellent in reducing the central load and computational time.

Implementation and Verification of 5G Network Slicing for Smart Grids

In this paper, 5G slicing networks are proposed to be deployed to address the issues associated with current communication networks in power grid systems and to enable smart grid applications. 5G slice architecture and the corresponding schemes including radio resource reservation, QoS scheduling strategy, VLAN, VPN and 5QI are applied for the access network, the transport network and the core network in the system, based on which a real 5G slicing network is implemented for smart grid applications. It is shown by field trial that the performance requirement regarding service isolation, bandwidth, delay and reliability required by various smart grid applications can be satisfied using the proposed schemes in the real system.

Conceptual Evaluation of a 5G Network Slicing Technique for Emergency Communications and Preliminary Estimate of Energy Trade-Off

The definition of multiple slicing types in 5G has created a wide field for service innovation in communications. However, the advantages that network slicing has to offer remain to be fully exploited by today’s applications and users. An important area that can potentially benefit from 5G slicing is emergency communications for First Responders. The latter consists of heterogeneous teams, imposing different requirements on the connectivity network. In this paper, the RESPOND-A platform is presented, which provides First Responders with network-enabled tools on top of 5G on-scene planning, with enhanced service slicing capabilities tailored to emergency communications. Furthermore, a mapping of emergency services and communications to specific slice types is proposed to identify the current challenges in the field. Additionally, the proposed tentative mechanism is evaluated in terms of energy efficiency. Finally, the approach is summarized by discussing future steps in the convergence of 5G network slicing in various areas of emergency vertical applications.

Multi-tier multi-tenant network slicing: A multi-domain games approach

The 5G slice networks will play a critical role in meeting the stringent quality-of-service requirements of different use cases, reducing the Capital Expenditure (CapEX) and Operational Expenditure (OpEX) of mobile network operators. Owing to the flexibility and ability of 5G slice networks to meet the needs of different verticals, it attracts new network players and entities to the mobile network ecosystem, and therefore it creates new business models and structures. Motivated by this development, this paper addresses the dynamic resource allocation in a multi-slice multi-tier multi-domain network with different network players. The dynamic resource allocation problem is formulated as a maximum utility optimisation problem from a multiplayer multi-domain perspective. Furthermore, a 3-level hierarchical business model comprising Infrastructure Providers (InPs), Mobile Virtual Network Operators (MVNOs), Service Providers (SPs), and slice users are investigated. We propose two schemes: a multi-tier multi-domain slice user matching game scheme and a distributed backtracking multiplayer multi-domain game scheme in solving the transformed maximum utility optimisation problem. We compare the multi-tier multi-tenant multi-domain game scheme with a Genetic Algorithm (GA) Intelligent Latency-Aware Resource (GI-LARE) allocation scheme, and a static slicing resource allocation scheme via Monte Carlo simulation. Our findings reveal that the proposed scheme significantly outperforms these other schemes.

Priority-Based Downlink Wireless Resource Provisioning for Radio Access Network Slicing

This paper examines network slicing within the radio access network which employs an orthogonal frequency division multiple access system for downlink communications. Its radio resources are allocated among slices configured for specific 5G use cases as well as other non-5G services. This work sets out to achieve optimal resource provisioning and power allocation within the context of priority slicing where slices are assigned priority levels by the base station. A mixed-integer non-linear programming problem is formulated to maximize the throughput of a best effort slice while satisfying the constraints of the high priority 5G slices. The problem is simplified and relaxed into a convex optimization problem. Three scenarios under various conditions are presented to serve as benchmarks. The impact of the chosen schedulers on the allocations, intra-slice, and inter-slice contentions is also examined. The results highlight that the wireless network can satisfy the quality-of-service requirements of opposing levels of priorities of traffic while simultaneously mitigating both inter-slice and intra-slice contentions under conditions mirroring that of practical wireless network deployments. Furthermore, it is proven that the convex approximation problem serves as a reasonable approximation of the original MINLP problem.

Research on intelligent logic design and application of campus MMTC scene based on 5G slicing technology

A consensus has been reached that 5G network slicing technology is becoming increasingly important in EMBB, MMTC and URLLC. However, this technology still has a long way to go in education industry. By selecting four types of demands in campus MMTC scenarios as specific application references, this research explores the architectural relationship between network slicing layer, intelligent terminal layer and application capability layer. Besides, emphasis has been put on the influences that virtual logic network design technology, isolation technology and standard technology has on application experiences. Under such goal, a two-dimensional route has been proposed to deploy network slicing technology based on the concept of full life cycle and the synergistic effect that AI algorithms has on slicing technology. This research is expected to nurture slicing technology, not only its technology chain, but more importantly, facilitate its value chain and large-scale vertical industry applications.

Quality of perception prediction in 5G slices for e-Health services using user-perceived QoS

In order to compete for a prominent market share, network operators and service providers should retain and increase the verticals’ subscription, catering to their needs in order to differentiate themselves from competitors. In this scenario, verticals’ satisfaction arises of paramount importance. As such, user experience is becoming a reliable indicator for service providers and telecommunication operators to convey overall end-to-end system functioning. To properly estimate end user satisfaction, operators and service providers require efficient means for quality monitoring and estimation at all layers, in conjunction with mechanisms able to maintain said quality at optimum levels. Given these factors, this paper proposes a mechanism for Quality of Perception (QoP) estimation in e-Health services, enabling the QoP-aware management of network slices fulfilling the requirements of supported services. To this end, the paper proposes a cognitive-based architecture which allows for the collection and monitoring of verticals’ data to estimate QoP and provides mechanisms to re-configure the underlying network slices according to the monitored quality levels. A machine learning (ML) model is introduced that aims to forecast any future degradation in the quality perceived by vertical users. In case of a predicted degradation, the proposed architecture reacts and triggers the necessary remedial actions, referred as actuations. In order to evaluate the developed ML model and to showcase the interaction between the different components of the proposed architecture, an experimental study is presented with real data extracted from a roaming ambulance. In addition, a Proof of Concept of the actuation mechanism is demonstrated through an experimental testbed emulating e-Health services.

Research on Vehicle-Road Co-Location Method Oriented to Network Slicing Service and Traffic Video

The development of 5G network slicing technology, combined with the application scenarios of vehicle–road collaborative positioning, provides end-to-end, large-bandwidth, low-latency, and highly reliable flexible customized services for Internet of Vehicle (IoV) services in different business scenarios. Starting from the needs of the network in the business scenario oriented to co-location, we researched the application of 5G network slicing technology in the vehicle–road cooperative localization system. We considered scheduling 5G slice resources. Creating slices to ensure the safety of the system, provided an optimized solution for the application of the vehicle–road coordinated positioning system. On this basis, this paper proposes a vehicle–road coordinated combined positioning method based on Beidou. On the basis of Beidou positioning and track estimation, using the advantages of the volumetric Kalman model, a combined positioning algorithm based on CKF was established. In order to further improve the positioning accuracy, vehicle characteristics could be extracted based on the traffic monitoring video stream to optimize the service-oriented positioning system. Considering that the vehicles in the urban traffic system can theoretically only travel on the road, the plan can be further optimized based on the road network information. It was preliminarily verified by simulation that this research idea has improved the relative single positioning method.