Integration of Network Slicing and Machine Learning into Edge Networks for Low-Latency Services in 5G and beyond Systems (original) (raw)
Related papers
Network Slicing in 5G Systems: Challenges, Opportunities and Implementation Approaches
IJIRIS:: AM Publications,India, 2024
The introduction of the fifth-generation (5G) of network technology has radically transformed the telecommunications landscape by providing high-speed, low-latency communication suitable for a range of innovative applications. However, this transformation also introduces novel network complexity and resource management challenges. An emerging solution to these formidable challenges is 'Network Slicing,' a powerful technology that plays a crux role in the efficient management of 5G network systems. Network slicing, enabled by key technologies such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), allows the creation of multiple virtual and independent networks operating on a shared physical infrastructure. This ability contributes to a more flexible, scalable, and efficient network system, making it aptly suited for diverse 5G applications. In this paper, we conduct an indepth examination of network slicing in 5G systems, its implementation strategies, associated challenges, and potential solutions. Two real-world case studies underline its practical applications, while a discussion on the future outlook anticipates advances in AI and ML to refine network slicing management. The paper posits that while network slicing brings its own set of complexities, its continuous evolution and relentless innovations gear towards overcoming such challenges, paving the way to a future of 5G networking marked by versatility, reliability, and efficiency of unprecedented levels.
Network slicing for 5G edge services
Internet Technology Letters
In the current 5G technology domain network slicing already plays an important role as a critical enabler. An industry that 5G aims to disrupt is the vehicular one. In this paper the brief scope of the 5G-DRIVE research project is presented, regarding 5G vehicular research between the EU and China. In the frame of 5G-DRIVE a set of slicing mechanisms are investigated and evaluated in regard to their performance. Firstly, related to slicing mechanisms in the NFV domain the OSM orchestrator is measured in terms of scalability and performance. In the next experimental set related to RAN slicing, the Katana Slice Manager is evaluated and depicts how different slicing configurations can achieve different performance results. Furthermore, the paper showcases how 5G network slicing can be integrated as a key enabler to the stringent demands of a vehicular network environment. Finally, the paper concludes, setting future directions in the related field.
Network Slicing for Beyond 5G Systems: An Overview of the Smart Port Use Case
Electronics, 2021
As the idea of a new wireless communication standard (5G) started to circulate around the world, there was much speculation regarding its performance, making it necessary to carry out further research by keeping in view the challenges presented by it. 5G is considered a multi-system support network due to its ability to provide benefits to vertical industries. Due to the wide range of devices and applications, it is essential to provide support for massively interconnected devices. Network slicing has emerged as the key technology to meet the requirements of the communications network. In this paper, we present a review of the latest achievements of 5G network slicing by comparing the architecture of The Next Generation Mobile Network Alliance’s (NGMN’s) and 5G-PPP, using the enabling technologies software-defined networking (SDN) and network function virtualization (NFV). We then review and discuss machine learning (ML) techniques and their integration with network slicing for beyo...
IEEE Access
Fifth-Generation (5G) mobile cellular networks provide a promising platform for new, innovative and diverse IoT applications, such as ultra-reliable and low latency communication, real-time and dynamic data processing, intensive computation, and massive device connectivity. End-to-End (E2E) network slicing candidates present a promising approach to resource allocation and distribution that permit operators to flexibly provide scalable virtualized and dedicated logical networks over common physical infrastructure. Though network slicing promises the provision of services on demand, many of its use cases, such as self-driving cars and Google's Stadia, would require the integration of a Multi-Access Edge Computing (MEC) platform in 5G networks. Edge Computing is envisioned as one of the key drivers for 5G and Sixth-Generation (6G) mobile cellular networks, but its role in network slicing remains to be fully explored. We investigate MEC and network slicing for the provision of 5G service focused use cases. Recently, changes to the cloud-native 5G core are a focus with MEC use cases providing network scalability, elasticity, flexibility, and automation. A cloud-native microservices architecture, along with its potential use cases for 5G network slicing, is envisioned. This paper also elaborates on the recent advances made in enabling E2E network slicing, its enabling technologies, solutions, and current standardization efforts. Finally, this paper identifies open research issues and challenges and provides possible solutions and recommendations. INDEX TERMS Network slicing, software defined networking, multi-access edge computing, cloud native, ultra-reliable, and low latency communication.
An end-to-end network slicing framework for 5G wireless communication systems
ArXiv, 2016
Wireless industry nowadays is facing two major challenges: 1) how to support the vertical industry applications so that to expand the wireless industry market and 2) how to further enhance device capability and user experience. In this paper, we propose a technology framework to address these challenges. The proposed technology framework is based on end-to-end vertical and horizontal slicing, where vertical slicing enables vertical industry and services and horizontal slicing improves system capacity and user experience. The technology development on vertical slicing has already started in late 4G and early 5G and is mostly focused on slicing the core network. We envision this trend to continue with the development of vertical slicing in the radio access network and the air interface. Moving beyond vertical slicing, we propose to horizontally slice the computation and communication resources to form virtual computation platforms for solving the network capacity scaling problem and e...
Survey on Machine Learning-Enabled Network Slicing: Covering the Entire Life Cycle
IEEE Transactions on Network and Service Management
Network slicing (NS) is becoming an essential element of service management and orchestration in communication networks, starting from mobile cellular networks and extending to a global initiative. NS can reshape the deployment and operation of traditional services, support the introduction of new ones, vastly advance how resource allocation performs in networks, and notably change the user experience. Most of these promises still need to reach the real world, but they have already demonstrated their capabilities in many experimental infrastructures. However, complexity, scale, and dynamism are pressuring for a Machine Learning (ML)-enabled NS approach in which autonomy and efficiency are critical features. This trend is relatively new but growing fast and attracting much attention. This article surveys Artificial Intelligence-enabled NS and its potential use in current and future infrastructures. We have covered state-of-the-art ML-enabled NS for all network segments and organized the literature according to the phases of the NS life cycle. We also discuss challenges and opportunities in research on this topic.
Fog Computing for Network Slicing in 5G Networks: An Overview
Asrar Baktayan, Malek AlGabri, Sharaf Alhomd, 2018
5G is visualized to be a multi-service network assisting a huge range of modern-day technologies with a different set of performance and service requirements. Slicing a single physical network into multiple isolated logical networks has provided as a key concept to realizing this vision. Fog computing is a new paradigm to expand the IoT devices that extends computation, communication, and storage functions towards the edge in 5G networks. This study gives a literature on fog computing importance in various 5G network slicing predicated on a detailed description of network slicing, covering three different application domains (i.e., mMTC, eMBB, and uRLLC), also provides a high-level addressing of a multi-slice environment that helps network slicing to provide the appropriate customization and highlight the technology challenges and research directions.
Machine Learning in Network Slicing - A Survey
5G and beyond networks are expected to support a wide range of services, with highly diverse requirements. Yet, the traditional “one-size-fits-all” network architecture lacks the flexibility to accommodate these services. In this respect, network slicing has been introduced as a promising paradigm for 5G and beyond networks, supporting not only traditional mobile services, but also vertical industries services, with very heterogeneous requirements. Along with its benefits, the practical implementation of network slicing brings a lot of challenges. Thanks to the recent advances on Machine Learning (ML), some of these challenges have been addressed. In particular, the application of ML approaches is enabling the autonomous management of resources, in the network slicing paradigm. Accordingly, this paper presents a comprehensive survey on contributions on ML in network slicing, identifying major categories and sub-categories in the literature. Key takeaways are also presented and open ...
IEEE Wireless Communications, 2019
5G services, such as Ultra-reliable and Low Latency Communications, Massive Machine Type Communications and Enhanced Mobile Broadband, support low (or ultra-low) latency, a huge number of connections, and high bandwidth. Typically, 5G platforms are shared by multiple tenants, where each tenant has different service deployment requirements and thus requires different amounts of resources from the lower tier (i.e., radio access network and mobile edge) and upper tier (i.e., transport network and central office) of the 5G architecture. Consequently, slicing is a key technology in 5G networks for providing scalability and flexibility in allocating the 5G resources with appropriate isolation. This study proposes an Endto-End Slicing as a Service framework for slicing both computing and communication resources across the full 2-tier multi-access edge computing architecture. The framework is implemented using open source tools. It is shown that the framework successfully isolates the 5G resources, which are computing and communication, between slices (slicing isolation effect ratio equals 1) and ensures that resources of the deployed slices are merely sufficient to meet the latency requirements of the tenants. Moreover, the experiments show that URLLC and mMTC services require more than 70 percent of the needed computing and communication resources be provided by the edge and RAN in order to satisfy their tighter latency requirements. Overall, the results suggest a central to edge resource allocation ratio of 9:1, 3:7, and 1:9 for the eMBB, URLLC, mMTC applications, respectively. Therefore, the resources in the edge and RAN are critical.
A Comprehensive View of State-of-Art of 5G Network Slicing
Journal of network and information security, 2020
Network Slicing is a concept that creates multiple virtual networks that serve the purpose of various service requirements. These logical networks created on top of the same physical network infrastructure are called "network slices". Each slice of the network acts as an isolated network that is end-to-end and customized to achieve the requirements as expected by the application. This network slicing is one of the driving aspects in the 5G networks, which promises to provide various services as per the user requirement. A study is made on Network Function Virtualization (NFV) and Software Defined Networks (SDN) which forms the driving aspects for network Slicing in 5G networks. Also, the state of art developments in the field of network slicing has been studied and explained. The paper presents the benefits of 5G network slicing from the technical point of view and later describes different vertical segments that make use of slicing of 5G networks. It can be stated that network slicing in 5G networks offers to improve the efficiency of the 5G networks and also helps to achieve the expected and promised performance of the 5G in the coming future.