Comprehensive Analysis of Network Slicing for the Developing Commercial Needs and Networking Challenges
Abstract
:1. Introduction
1.1. Significance of Network Slicing
1.2. Fifth-Generation Use Cases
1.3. Network Slicing Classifications
1.4. Major Contributions and Paper Organization
- Highlight 5G orchestration architecture, and the applicability of cloud-native supporting technologies.
- A thorough explanation of the significance of NS characterization is needed to design complete NS solutions. Additionally, we present a description of the technical and functional purpose of NS.
- Recent efforts are being made to support prospects for service providers.
- Provides a view into the AI- and ML-related activity taken on in various SDOs and commercial forums, and finally discussed the open research challenges faced by CSPs.
2. Network Slicing from a Business Standpoint
2.1. Limitations and Challenges for Businesses Adopting 5G Technology
- 5G—A virtual adaptable networkThe vast majority of 5G “non-standalone” installations presently rely on the existing 4G infrastructure. However, the industry is building a new network concept to realize the promise of 5G. The 5G core will be a “cloud-native”, Its underlying technologies SDN and NFV will virtualize basic network components. Furthermore, virtualization introduces new security issues since when a network is implemented in software, there is a risk of cross-contamination and data leakage. Automation can accelerate the spread of inaccurate judgments and illnesses.
- Digitalization of customer connectionsTelcos must investigate virtual alternatives that deliver attractive services to clients who are not there in person. Data are crucial in any situation. A mobile network operator (MNOs) should be able to examine digital interactions with the network to help comprehend individual subscribers’ behavior. With this information, businesses can give customized digital services.
- Large-scale deployments of linked products are now feasibleThe bulk of IoT devices are inexpensive, light, have little computational capability, and are powered by batteries. They should last for an extended period under challenging circumstances. The diversity of data connections is an additional factor. Some devices require low-bandwidth communication over short distances. Others demand sending brief, high-bandwidth bursts over considerable distances [20].
- Businesses acquire communications freedomBusinesses will be adept to manage their private network slices in a 5G future. However, running an in-house network requires security knowledge since it creates sensitive data that must be protected both in transit and at rest. To assist, telecommunications companies must ensure that only authorized persons have access to this information. They can collaborate with these businesses as “security as a service” partners. Previously, MNOs concentrated on enhancing smartphone security. They will need to enhance their skills across different device kinds and industrial sectors in the 5G future.
- Information structure must be cybersecureThe 5G network is the first mobile technology to launch in the era of global cybercrime conducted by professional syndicates. The virtual structure of the 5G network core provides these attackers with additional access opportunities. Because of virtualization, data no longer kept centrally but at the “edge." The 5G network also dramatically increases the number of linked devices.
2.2. Network Slice Lifecycle Management
- Preparation: this stage involves creating a network slice template, planning network slice capacity, onboarding, evaluating access network requirements, configuring the communication network, and performing any other prerequisite preparations before beginning an NSI.
- Commissioning: building the NSI is a part of provision at the assigned level. All essential responsibilities are scheduled and adjusted to fit the network slice criteria whenever an NSI is generated. The development and/or change of NSI components may be completed as part of the creation process.
- Operation: this phase comprises the initiation, management, performance reporting, improve resource allocation, customization, and termination of an NSI throughout the operation phase.
- Decommissioning: includes deactivating non-shared constituents as needed, as well as removing NSI-specific settings from common constituents. After the decommissioning procedure, the NSI is terminated and no longer exists.
3. Fifth-Generation Orchestration Framework
- Communication Service Management Function (CSMF): manages to transform communication service needs into network slice demands.
- Network Slice Management Function (NSMF): manages network slice templates (NSTs) including lifecycle management. The network slice subnet parameters are inferred from the network slice specifications.
- Network Slice Subnet Management Function (NSSMF): responsible for the management of NSIs
- NF Management Function (NFMF): responsible for application-level managing of virtual network functions (VNFs) and physical network functions (PNFs) and is a manufacturer of the provisioning solution that offers configuration management (CM), fault management (FM), and performance management (PM) [25].
3.1. Integrating 5G Orchestration with ETSI NFV
- The NFV orchestrator (NFVO) oversees orchestrating and managing the NS installed on the network functions virtualization infrastructure (NFVIs).
- The VNF manager directs the life-cycle management (LCM) of one or more VNFs. It is possible to deploy multiple VNF managers.
- The virtualized infrastructure manager (VIM) administers coordinating the functions needed to regulate and manage a VNF’s interface with computing, storage, and network resources, as well as their virtualization. Multiple VIM instances, one for each type of NFVI technology, might be implemented.
3.2. Cloud-Native Powering the Communication Industry’s Digital Transformation
3.3. Cloud-Native Empowering Technologies for NS
- ContainersWhen it comes to standalone 5G networks, a variety of the world’s top mobile carriers are investigating a cloud-native network design combined with containers (lightweight virtualization alternative to virtual machines (VMs). Containers, as opposed to virtual machines, can reduce costs by packaging only the OS needs particular to a certain application. Docker is one of the most widely used containerization systems because to its versatility and scalability. Additionally, it is considered as a significant element of an NFV architecture, the main enabling technology for NS [27].
- KubernetesKubernetes is a container orchestrator created by Google that contributed to the CNCF and is now open source. It benefits from Google’s years of experience in container management. It is a comprehensive solution for handling containerized application deployment, scheduling, and scaling, and it supports various containerization technologies, including Docker. Kubernetes-related services, support, and tools are widely available. It does not directly execute containers; rather, encapsulates one or more containers in a high-level architecture known as pods [28].
- OpenStackOpenStack is widely used for private and public cloud deployment by organizations of all sizes. Different solution suppliers implemented OpenStack for various 5G installations in the telecom sector. Over the last few years, OpenStack has been implemented on nine out of ten of the world’s largest telecom networks. It is also known as a cloud OS since it maintains and uses huge pools of resources in data centers, such as computing, networking, and storage [29].
4. Technical and Functional Realization of NS
- Network Slice Selection Function (NSSF): appoints NSIs for the UE. Determines the AMF configured to service the UE.
- Network Exposure Function (NEF): allows third-party programs to connect to the network in a secure manner.
- Network Resource Function (NRF): ensures that records of services given by other NFs kept up to date.
- Policy Control Function (PCF): to manage network performance, an integrated policy structure used. Control plane policy guidelines provided.
- Unified Data Management (UDM): authentication and key agreement (AKA) credentials generated. Access granted depending on subscription data.
- Application Function (AF): traffic routing choices, NEF accessibility, and strategic framework interactions are all managed through interfaces with the 3GPP core network.
- Access and Mobility Management Function (AMF): licensing, permissions, and mobility management are all part of the AMF process.
- Session Management Function (SMF): Protocol data unit (PDU) sessions created, updated, or deleted.
- Authentication Server Function (AUSF): authorization for 3GPP connection and non-3GPP connection that not trusted.
- User Plane Function (UPF): redirecting and placement of user-plane packets. Mobility’s securing point.
- Binding Support Function (BSF): connects an AF request to the appropriate PCF.
4.1. Concept of 5G SBA Registration
4.2. Concept of 5G SBA PDU Session
4.3. Fifth-Generation NS Projects and Opportunities for Service Providers
5. Integrating Artificial Intelligence and Machine Learning for NS
6. Open Research Areas and Future Directions
- RAN re-structuring and spectrum slicingMicrocells and macrocells must be redesigned to function in rationally defined slices. As the slices need to provide all access regardless of whether on Wi-Fi or on small cells or large-scale cells since appropriate co-appointment is required for the handover of sessions across slices. If a vehicle’s original equipment manufacturer (OEM) takes a slice, the administrator must allocate end-to-end network assets over every geographic district. Since the spectrum is additionally a mutual asset. This kind of committed provision is expensive. There is a need to develop a model for the enterprise customers that conveys the ideal QoE while still guaranteeing income for the administrator.
- Service assurance and managementIt is difficult to meet the SLAs established for each slice at each point in the system while using NS. If low latency is guaranteed, for example, the client should be able to get it. Similarly, while allocating slices, operators should ensure that unique slices adhere to the measuring system. Each slice must be scaled and monitored separately, and the slices must ensure QoS is fulfilled. Interoperability issues must be addressed when slices include a significant number of suppliers.
- Cloud-native 5G core’s adaptabilityThe agility of the 5G core is essential to leverage cloud-native features such as automated processes, adaptive application and NF scaling, and greater utilization of storage and processing resources. The goal is to offer a completely compatible, scalable packet processing solution for containers.
- Containers and VMs hybridizationMaking NFs cloud-native might not be feasible since not all applications would benefit. The future may lie in the integration of the two technologies. To build an orchestration platform that can connect two distinct kinds of workloads, such as OpenStack and Kubernetes, more study is required.
- Network slice isolationThe 5G mobile network is intended to enable the construction of network slices that might give access to third-party entities, such as companies. Developing an effective strategy to ensure isolation across various pods and services is a requirement for hosting extremely sensitive services in a network.
- Dynamic service positioningThe 5G SBA is anticipated to comprise modular, dynamically connected NFs and services. Every service may offer a diverse set of features depending on the demands and service type. The self-contained smaller and more modular NFs joined and freely linked to instantiate an E2E network slice [55].
- Administration trust among multiple regulatory domainsNS integration across various domains is a considerable challenge. In a situation with high mobility and the demand for uRLLC slicing, distributed slicing is necessary. The handling of security and trust across numerous vendors and several administrative domains that share physical resources must be investigated [56].
- Edge intelligence and consumer estimationThe objective of NGWN is to make it possible for AI to employ wireless connectivity in scenarios such as self-learning networks and deep reinforcement learning (DRL). The idea of using the network edge wireless link is to develop effective and innovative neural network architectures [57].
- Adaptive business mobilityThe transfer of services used by a set of mobile users takes few seconds instead of the expected microseconds for the uRLLC slice’s E2E latency. When users relocate across the network, service migration might be costly, occupy limited bandwidth, and the target edge cloud may lack the resources needed to maintain the service continuity [58].
- Efficient resource utilization using MLML methods, such as support vector machine (SVM) and DRL, are still to be managed efficiently in NS. SVM, for example, may use to aid in network slice selection by classifying service demands.
- Controller placement solutions and isolationThe 5G core NFs may place in any geographical area across public, regional, or private DCs. The task is to determine the best assignment policy for the E2E network slice controller. The ideal number of controllers necessary is an outstanding issue that needs to study. Instead of a shared control plane, the issues are in providing an independent and tailored control plane for each customer. Consequently, the vertical business will be able to develop a tailored control programmed to satisfy the demands of its customers.
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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SST | SST Value | Expected Features |
---|---|---|
eMBB | 1 | Extreme throughput Improved spectral efficiency Expanded coverage |
uRLLC | 2 | High reliability Low latency High accessibility Place accuracy |
mIoT | 3 | Higher linking density Fewer complication Prolonged coverage |
Studies | Applications | Classes | Business View | Orchestration | Cloud-Native Tools | Functional Realization | AI and ML | Challenges | Projects |
---|---|---|---|---|---|---|---|---|---|
[11] | ✓ | ✕ | ✕ | ✓ | ✕ | ✕ | ✕ | ✓ | ✕ |
[12] | ✓ | ✕ | Limited | ✓ | ✓ | ✓ | ✕ | ✓ | ✕ |
[13] | ✓ | ✕ | ✕ | ✓ | ✕ | ✕ | ✕ | ✓ | ✕ |
[14] | ✓ | ✕ | Limited | ✓ | ✕ | ✕ | Limited | ✓ | ✕ |
[15] | ✓ | ✓ | Limited | ✕ | Limited | ✕ | ✓ | ✓ | ✓ |
Our Work | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Acronyms | Full Form | Acronyms | Full Form | Acronyms | Full Form |
---|---|---|---|---|---|
NS | Network Slicing | uRLLC | Ultra-Reliable Low Latency Communication | VM | Virtual Machine |
CSPs | Communication Service Providers | SST | Slice/Service Type | SBA | Services Based Architecture |
AI | Artificial Intelligence | E2E | End-to-End | NFs | Network Functions |
ML | Machine Learning | CAGR | Compound Annual Growth Rate | UE | User Equipment |
NGWN | Next Generation Wireless Network | MNOs | Mobile Network Operators | NRF | Network Resource Function |
MEC | Mobile Edge Computing | NSaaS | Network Slice as a Service | UDM | Unified Data Management |
IoT | Internet of Things | CN | Core Network | AF | Application Function |
3GPP | Third Generation Partnership Project | TN | Transport Network | AMF | Access and Mobility Management Function |
SDO | Standard Developing Organization | RAN | Radio Access Network | SMF | Session Management Function |
QoS | Quality of Service | CSI | Communication Service Instance | PDU | Protocol data unit |
AR | Augmented Reality | NSSI | Network Slice Subnets Instances | UPF | User Plane Function |
APN | Access Point Name | CSMF | Communication Service Management Function | AUSF | Authentication Server Function |
EUTRAN | Evolved UMTS Terrestrial Radio Access Network | NSMF | Network Slice Management Function | BSF | Binding Support Function |
EPC | Evolved Packet Core | NSSMF | Network Slice Subnet Management Function | PCF | Policy Control Function |
DCN | Dedicated Core Network | NFMF | NF Management Function | DHCP | Dynamic Host Configuration Protocol |
SDN | Software Defined Networking | VNF | Virtual Network Function | PDN | Packet Data Network |
NFV | Network Function Virtualization | PNF | Physical Network Function | DN | Data Network |
RAN | Radio Access Network | MANO | Management and Orchestration | CM | Configuration Management |
SLA | Service Level Agreement | NFVO | NFV Orchestrator | FM | Fault Management |
GSMA | Global System for Mobile Communications | NFVIs | NFV Infrastructure | ISG ENI | Industry Specification Group on Experiential Networked Intelligence |
NSI | Network Slice Instance | LCM | Life Cycle Management | BPM | Business Process Management |
ITU | International Telecommunication Union | VIM | Virtualized Infrastructure Manager | DRL | Deep Reinforcement Learning |
eMBB | Enhanced Mobile Broadband | CNCF | Cloud-Native Core Network | SVM | Support Vector Machine |
Performance | Operational | Functional | |
---|---|---|---|
Business Constraints | Throughput | Design and extensive process capacity | Isolation and flexibility |
Latency | SLAs and active preservation | Placement and delay tolerance | |
Synchronization | Supervision potential | Security |
Project Name | Application Areas | Tools SDN, NFV | Features | Objectives |
---|---|---|---|---|
5G-XHAUL (2015–2018) [32] | Automotive, e-health | ✓,✓ | NS concept and administration | Create a robust SDN control plane and request statistical models that are agility smart for optical/wireless 5G networks. |
5G!PAGODA (2016–2019) [33] | IoT, human Interaction | ✓,✓ | Coherent architecture | The primary goals are to create a consistent infrastructure that allows Europe and Japan to collaborate on research and standards. The suggested innovations are designed to work with a common SDN/NFV-based architecture. |
5G-MoNArch (2017–2019) [34] | Smart cities, industry 4.0 | ✓,✓ | Software development and validation kits | Developed a detailed NS framework and used its flexibility to fully integrate functionalities necessary for industrial, media and entertainment, and smart city use cases. |
ONE5G (2017–2019) [35] | Agricultural, automotive | ✓,✓ | NS design and management | To suggest enhanced network skills and modifications ahead of release fifteen to allow multi-service function and functional execution of “5G advanced (pro),” including upcoming network applications, advanced massive MIMO enablers, and link control. |
SLICENET (2017–2020) [36] | Smart cities, e-health, smart grid | ✓,✓ | Software development and support | Generate a platform for smart network control, governance, and orchestration in SDN/NFV-enabled 5G networks to support infrastructure exchange across multiple operator domains. |
5G-TANGO (2017–2020) [37] | Broadcasting, real-time comms, industry 4.0 | ✓,✓ | _____ | Provides commercial prospects through network adaptation and adaptation to vertical technical standards by decreasing the access barrier for third-party designers and enabling the building and integration of virtual network functions (VNFs) and application elements as “network services”. |
MATILDA (2017–2019) [38] | Media, smart cities, automotive, industry 4.0 | ✓,✓ | _____ | Design a fundamental shift in the development of software for 5G-ready solutions, as well as virtual and physical network operations and network services. A cross virtualized infrastructure manager helps to manage cloud/edge computing and IoT resources from various locations. |
5GCity (2017–2019) [39] | Smart cities, neutral masses, broadcasting | ✓,✓ | _____ | Optimize the financial return for the whole virtual market chain and to deploy a common, multi-tenant, open forum that expands the (consolidated) cloud model to the network’s outer limit. |
5G ESSENCE (2017–2020) [40] | Entertainment, public safety | ✓,✓ | _____ | Manages the concepts of small cell as a service and edge cloud technology via enabling the drivers and reducing obstacles in the small cell industry, which anticipated to expand quickly and play a key role in the 5G ecosystem. |
5G-TRANSFORMER (2017–2020) [41] | E-health, media, and entertainment, automotive | ✓,✓ | NS design and organization | Create a 5G network architecture centered on SDN/NFV that tailored to certain vertical sectors. |
5GMobix (2018–2021) [42] | Associated and autonomous driving | ✕,✕ | Automated vehicle functionalities | Intends to link the benefits of 5G technology with sophisticated connected autonomous mobility applications to allow novel, traditionally implausible, autonomous car applications, both technically and commercially. |
Primo-5G (2018–2021) [43] | Smart firefighting | ✕,✕ | Network framework | Demonstrate a comprehensive 5G system capable of providing interactive virtual solutions for moving items, achieved with cross-continental testbeds that connect radio access and core networks built by different project participants. |
5G DRONES (2019–2022) [44] | eMBB, mIoT, uRLLC | ✕,✕ | Innovative developments | The drones intended to assess various UAV use-cases for eMBB, uRLLC, and mIoT 5G services as well as validate 5G KPIs for supporting them. The project will build on the ICT-17 projects’ 5G infrastructure and number of support locations while also identifying and developing the remaining elements. |
INSPIRE-5Gplus (2019–2022) [45] | Self-directed and connected vehicles to critical industry 4.0 | ✕,✓ | System framework, protection, and isolation | Intends to bring a significant shift in the access control of 5G networks and well beyond at the platform, vertical application, and quality of service. |
AutoAir (2019) [46] | Authentication and advancement of associated and independent automobiles | ✕,✕ | System framework | Allow the testing and deployment of self—driving technology. In addition to requiring more network bandwidth than is currently available, fast travel speeds hinder cell-tower handoff. It will also look at whether these 5G connection options may be applied to both road and rail transportation. |
MonB5G (2019–2022) [47] | Zero-touch processing and planning across business zones | ✕,✕ | E2E orchestration and protection | Allow NS at enormous sizes for 5G LTE and beyond, offer zero-touch administration and orchestration. |
Semantic (2020–2023) [48] | Multi-GHz range networks, MEC-enabled use provisioning and E2E | ✕,✕ | E2E orchestration | Presents a unique research training system for multi-Ghz limit connectivity, MEC enabled approach encompasses, and E2E NS, all integrated and jointly managed with forward data service automatic control that powers the large amounts of portable BIG DATA triggered into the cellular connection. |
Hexa-X (2021–2023) [49] | Sustainable growth, huge linking, tele-presence, and regional trust areas | ✕,✓ | System framework, scalability, protection, and orchestration | Aims to create leading technology enablers in the following areas: inherently new radio access techniques at high frequencies and resolution segmentation and sensor-based; integrated smartness via AI-driven radio interface and management for large scale deployments; 6G structural enablers for system partitioning and flexible reliability. |
Projects | Objectives |
---|---|
ETSI ISG ENI [50] | The Industry Specification Group on Experiential Networked Intelligence (ISG ENI) manages establishing policies that use AI mechanisms to improve the operator practical experience by identifying and combining evolving knowledge, allowing operators to make more prompt decisions, and aiding in network management and orchestration. |
ITU FG-ML5G [51] | The goal of the ML5G Focus Group was to undertake an ML evaluation for future networks and to highlight significant gaps and concerns in standardized processes associated with this topic. In addition, technical elements such as use cases, requirements, and architectures are examined. The Focus Group operated as an open venue for specialists from ITU members and non-members to go forward with ML research linked to future networks, including 5G. |
ISO/IEC JTC 1/SC42 [52] | Establish a set of standards for determining the context, resources, and processes for creating and deploying AI applications. It can be used by ISO, IEC, and JTC1 technical committees and subcommittees to expand on this work in developing standards for AI applications in their respective areas of interest. The recommendations give a high-level overview of the AI application environment, stakeholders and their responsibilities, the system’s life cycle, and common AI application features. |
TM Forum Smart BPM [53,54] | SMART business process management (BPM) enables digital transformation catalyst who has previously proved the benefits of automated operations. This was accomplished through a business “process mining” and the instruments of adaptive discovery and orchestration of workflows. The use of analytics and big data also provided insights that enabled to leverage of user experience and network optimization. |
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Zahoor, S.; Ahmad, I.; Othman, M.T.B.; Mamoon, A.; Rehman, A.U.; Shafiq, M.; Hamam, H. Comprehensive Analysis of Network Slicing for the Developing Commercial Needs and Networking Challenges. Sensors 2022, 22, 6623. https://doi.org/10.3390/s22176623
Zahoor S, Ahmad I, Othman MTB, Mamoon A, Rehman AU, Shafiq M, Hamam H. Comprehensive Analysis of Network Slicing for the Developing Commercial Needs and Networking Challenges. Sensors. 2022; 22(17):6623. https://doi.org/10.3390/s22176623
Chicago/Turabian StyleZahoor, Sumbal, Ishtiaq Ahmad, Mohamed Tahar Ben Othman, Ali Mamoon, Ateeq Ur Rehman, Muhammad Shafiq, and Habib Hamam. 2022. "Comprehensive Analysis of Network Slicing for the Developing Commercial Needs and Networking Challenges" Sensors 22, no. 17: 6623. https://doi.org/10.3390/s22176623
APA StyleZahoor, S., Ahmad, I., Othman, M. T. B., Mamoon, A., Rehman, A. U., Shafiq, M., & Hamam, H. (2022). Comprehensive Analysis of Network Slicing for the Developing Commercial Needs and Networking Challenges. Sensors, 22(17), 6623. https://doi.org/10.3390/s22176623