Network Slicing in 5G: Survey and Challenges

Network slicing is one of the key technologies for 5th-Generation (5G). It enables operators to construct network slices with similar qualities as dedicated stand-alone networks, but to realize them on a common physical platform. Meanwhile, the isolation among logical network slices can keep them from the negative impacts of other network slices. In this paper, we give an overview of the radio access network (RAN) slicing, and present some viewpoints on three categories of network slices. Moreover, an approach, which dynamically creates RAN slice to meet specific business and service requirements, is proposed. It does not only optimize performance and maximize resources utilization, but also shorten the creating time of slices.

Network slicing is a key technology in fifth-generation (5G) mobile networks. Slicing divides a physical network into multiple dedicated logical networks to meet the requirements of diverse use cases. Efficient slice deployment algorithms are critical in reducing network operators' costs and energy consumption and in providing users better service. Many researchers have focused on static deployment when investigating network slices, effectively ignoring network operators' requirements for the dynamic deployment and expansion of such slices. In this paper, we first construct a joint optimization problem of cost and energy consumption. Then, we propose a prediction-assisted adaptive network slice expansion algorithm to deploy network slices dynamically. The proposed algorithm consists of three parts. First, we devise a Holt-Winters (HW) prediction algorithm to determine traffic demand for network slices. This method is intended to avoid frequent changes in network topology. Second, we propose a virtual network function (VNF) adaptive scaling strategy to reasonably determine the number of VNFs and resources required for network slices to avoid resource wastage. Finally, we develop a proactive online algorithm to deploy network slices. This method deploys network slices reasonably via the VNF deployment algorithm and link-routing algorithm to ensure slices' service requirements. Resource capacity and delay requirements are also considered in our evaluation to ensure that network costs and energy consumption are minimized. We then perform a series of simulation experiments to compare the proposed method's performance to state-of-the-art dynamic network slicing technologies. Ultimately, our solution is deemed a suitable candidate for dynamic deployment of 5G network slices; the solution demonstrates advantages of high resource utilization, low deployment costs, and low energy consumption.

The increasing consumption of multimedia services and the demand of high-quality services from customers has triggered a fundamental change in how we administer networks in terms of abstraction, separation, and mapping of forwarding, control and management aspects of services. The industry and the academia are embracing 5G as the future network capable to support next generation vertical applications with different service requirements. To realize this vision in 5G network, the physical network has to be sliced into multiple isolated logical networks of varying sizes and structures which are dedicated to different types of services based on their requirements with different characteristics and requirements (e.g., a slice for massive IoT devices, smartphones or autonomous cars, etc.). Softwarization using Software-Defined Networking (SDN) and Network Function Virtualization (NFV)in 5G networks are expected to fill the void of programmable control and management of network resources.In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented. Moreover, we provide a discussion on various open source orchestrators and proof of concepts representing industrial contribution. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.

5G mobile networks encompass the capabilities of hosting a variety of services such as mobile social networks, multimedia delivery, healthcare, transportation, and public safety. Therefore, the major challenge in designing the 5G networks is how to support different types of users and applications with different quality-of-service requirements under a single physical network infrastructure. Recently, network slicing has been introduced as a promising solution to address this challenge. Network slicing allows programmable network instances which match the service requirements by using network virtualization technologies. However, how to efficiently allocate resources across network slices has not been well studied in the literature. Therefore, in this paper, we first introduce a model for orchestrating network slices based on the service requirements and available resources. Then, we propose a Markov decision process framework to formulate and determine the optimal policy that manages cross-slice admission control and resource allocation for the 5G networks. Through simulation results, we show that the proposed framework and solution are efficient not only in providing slice-as-a-service based on the service requirements, but also in maximizing the provider's revenue.

Upcoming 5G mobile systems are expected to meet the QoS requirements of a massive amount of devices with different service constraints. In this context, 5G networks can not rely on the monolithic architecture present in today’s networks. 5G mobile systems intend using network slicing to enable the creation of multiple logical networks (network slices) on top of a common physical infrastructure. These network slices are tailored according to the users’ service requirements. Network slicing can be deployed due to the consolidation of multiple technologies, such as NFV and SDN. This paper introduces a component named Slice Optimizer, implemented as an extension of LTE’s evolved NodeB, responsible to realize network slicing for LTE uplink transmission. The Slice Optimizer receives network slicing information from an Orchestrator, which is embedded in an SDN Controller. The Slice Optimizer, based on these network slicing information and on the current network state, selects the best slice to be scheduled at the moment. We performed extensive simulations to evaluate our proposal. The results show that our proposal can adapt to the network state, significantly increasing the user’s QoS experience.

Fifth Generation (5G) networks represent a transformative leap in the world of telecommunications, as they aim not only to increase data transfer speeds but also to establish a flexible infrastructure capable of accommodating the vast diversity of modern application and service requirements. At the heart of realizing this vision, network slicing technology emerges as one of the most significant architectural innovations that redefine how networks operate. However, this technology raises security concerns, which pose challenges that necessitate in-depth research and analysis. Therefore, it is essential to develop new security solutions that align with the dynamic nature of 5G networks, taking into account several security issues such as isolation between slices, authentication, and authorization. This study presents a systematic review of recent scientific research focusing on securing network slices in 5G environments. The review is based on peer-reviewed articles collected from trusted academic databases and offers practical and applicable recommendations to enhance 5G network security. The paper emphasizes the protection of network slicing technology from potential threats across three critical levels: Life-cycle Security, Intra-slice Security, and Inter-slice Security. The literature review highlights the extensive research interest in 5G network slicing, with particular attention to intelligent resource management using Deep Learning techniques such as the DeepSlice model to enhance network speed and flexibility. It also discusses the application of Lyapunov Stability Theory, a robust mathematical method to ensure system stability under data scarcity, and Multi-Agent Reinforcement Learning (MARL) for End-to-End resource management. Enabling technologies such as Network Function Virtualization (NFV) and Software Defined Networking (SDN) are identified as foundational pillars of network slicing. AI-based security solutions have been developed to accurately detect Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks. Some studies simulate attacks to analyze vulnerabilities and strengthen defenses using techniques like Federated Learning and Onion Routing combined with end-to-end encryption to ensure data confidentiality and anonymity within slices. This paper is the first prepared in Arabic in this field, providing a scientific review of the security aspects of network slicing. It selects scientific papers published over the past five years that focus on the security aspect of network slicing technology, contributing to enriching the Arabic scientific content in this specialization. Keywords: Network Slicing, 5G Networks, Slice Isolation, Authentication, Authorization, Security Threats, Virtual Networks, Life-cycle Security, Intra-slice Security, Inter-slice Security.

The future 5th generation (5G) mobile communication system will be required to support diverse services. Because of the difficulty in addressing the requirements of all these services using the same physical network, “network slicing,” which provides a customized logical network corresponding to service requirements, has recently attracted a great deal of attention. In the radio access network (RAN), the appropriate locations of base station functionalities to meet service requirements and achieve efficient network operation differ according to service type. Therefore, we have proposed a novel RAN slicing architecture, which has logical networks (slices) that choose an appropriate functional split option and its placement, to adjust to providing any service. This architecture achieves high flexibility and large scalability by employing a software-defined network and network function virtualization. A prototype is then developed based on the proposed architecture employing a unified controller of open-source software. It can construct slices for three service types: enhanced mobile broadband, ultra-reliable and low-latency communication, and massive machine-type communication, with flexibly located functionalities. In this paper, an experimental evaluation, considering the points of bandwidth consumption in midhaul, the impact of midhaul delay, communication latency, and isolation among slices, shows that the slices have specific performance benefits for each service type and also to achieve efficient network operation. This suggests that the proposed architecture is able to construct slices in a single infrastructure with different features according to the services required and to accommodate various services efficiently.

The 3rd Generation Partnership Project (3GPP) introduces network slicing for the provisioning of diverse network services in 5G. Additionally, boosted by cloud-based virtualization technologies, Network Function Virtualization (NFV) is also adopted in 5G to enhance scalability and elasticity. 5G network elements are evolving to cloud-native deployment. However, existing end-to-end (E2E) network slicing frameworks do not embrace cloud native yet. In this paper, we present a MANagement and Orchestration (MANO) framework for the automation of end-to-end (E2E) network slicing with the implementations of the core network (CN) and transport network (TN) slices. The framework is a showcase that follows 3GPP network slice management and 5G core network slicing mechanism, integrates novel bandwidth management techniques, and exploits all open-source approaches with state-of-the-art cloud native technologies. We evaluate the resource overhead of the framework and service throughput under bandwidth policies.

One of the Main expectation of the 5G environment is supporting various services in many areas such as healthcare, education, energy, streaming, V2X (vehicle to everything) communication, etc. To implement such an expectation, there is a need to assign dedicated resources and functionalities for each service by slicing the network which means creating a virtual network for each service inside a physical network. Each virtual network (Slice) should be isolated from the other virtual network (Slice), and the security of that slice becomes a core issue in most research and studies. In this study, after focusing on security challenges in network slices, we describe the network slicing idea, the isolation concept, and the enablers of the network slicing, as well as the prevention of related attacks, risks, and concerns in each enabler. The research also lists the previous surveys and maps out taxonomies to illustrate the contribution of each survey in presenting threats and attacks against network slicing.

Trade-off analysis between delay and throughput of RAN slicing for smart grid

Fifth-generation (5G) networks are already available in major urban areas and are expected to bring a major transformation to citizens’ lives. 5G services, such as enhanced mobile broadband (eMBB), ultra-reliable low latency communications (URLLC), and massive machine-type communications (mMTC), require a network infrastructure capable of supporting stringent requirements in terms of latency and bandwidth demands; as such, it must be highly dynamic and flexible. Network slicing is a key enabler technology that can provide dynamic and flexible characteristics to 5G network architecture. A network slice (NS) can be defined as a partition of network and IT resources, that is, network links and nodes capacity dedicated to a specific set of service demands. As a result, different NSs can coexist over the same physical infrastructure network and can be used to dynamically and flexibly deploy the aforementioned 5G services. However, to efficiently implement NSs with different requirements, communication service providers (CSPs) that own the physical infrastructure network must adopt sophisticated techniques for admission control and resource allocation of NSs. In this paper, we present a novel framework for admission control and resource allocation of 5G NSs in metro-core networks. Specifically, our framework is based on a deep reinforcement learning (DRL) algorithm called Advantage Actor Critic (A2C), which performs admission control, i.e. it is capable of learning which slice to admit based on the availability of the physical network resources. Then, given the diversity of requirements for each 5G service, we propose different resource allocation algorithms based on integer linear programming (ILP) and heuristics to treat each service accordingly. Results show that our proposed framework can increase the number of admitted NSs with respect to the case in which the admission control is disabled by improving the resource allocation performance.

Network slicing is a concept introduced in 5G networks that supports the provisioning of multiple types of mobile services with diversified quality of service (QoS) requirements in a shared network. Network slicing concerns the placement/allocation of radio processing resources and traffic flow transport over the Xhaul transport network—connecting the 5G radio access network (RAN) elements—for multiple services while ensuring the slices’ isolation and fulfilling specific service requirements. This work focuses on modeling and optimizing network slicing in packet-switched Xhaul networks, a cost-effective, flexible, and scalable transport solution in 5G RANs. The considered network scenario assumes two types of network slices related to enhanced mobile broadband (eMBB) and ultra-reliable low-latency communications (URLLC) services. We formulate a network slicing planning optimization problem and model it as a mixed-integer linear programming (MILP) problem. Moreover, we develop an efficient price-and-branch algorithm (PBA) based on column generation (CG). This advanced optimization technique allows for overcoming the MILP model’s poor performance when solving larger network problem instances. Using extensive numerical experiments, we show the advantages of the PBA regarding the quality of the solutions obtained and the computation times, and analyze the packet-switched Xhaul network’s performance in various network slicing scenarios.

Dynamic spectrum access (DSA) and network slicing are some of the principal concepts to realize the emerging applications in Beyond 5th Generation (B5G) and 6th Generation (6G) networks. The frequency spectrum remains scarce and underutilized, while the performance requirements in terms of data throughput and latency of the network tenants have diversified. DSA allows for the efficient utilization of spectrum resources, while network slicing aims to serve network users with highly distinctive service needs. Lack of incentivization, sharing of spectrum resources among multiple operators, and lack of trust between operators are some of the challenges faced by centralized DSA approaches. Similarly, secure network slice orchestration, slice-isolation, secure access to network resources, privacy of user sensitive data, assuring the provision of Service Level Agreements (SLAs), are some of the challenges in existing network slicing techniques. Blockchain due to its innate capabilities can be a promising technology to solve the key issues pertaining to current DSA and network slicing approaches. Blockchain through smart contracts, provides traceability of network resources, auditability and accountability of network operators and service providers. Smart contracts facilitate the automation of resource sharing and network slice orchestration, while ensuring that SLAs are met, and network operators are compensated. This paper first provides a comprehensive overview of the DSA concept, the existing DSA techniques, and the challenges posed by these techniques. This is followed by a detailed description of network slicing, its key elements and architecture, various network slicing parameters, existing network slicing techniques and their challenges. Then an in- depth review on blockchain, its working principle, factors that affect blockchain implementation, and a comparison of various open-source blockchain platforms that support smart contracts is presented. This discussion is summarized by presenting the state-of-the-art in the blockchain-enabled DSA and network slicing, challenges and trade-offs of these techniques, and the gaps and future directions in this research area. Finally, we conclude by providing some future research directions.

Internet of Things (IoT) is an emerging technology that makes people's lives smart by conquering a plethora of diverse application and service areas. In near future, the fifth-generation (5G) wireless networks provide the connectivity for this IoT ecosystem. It has been carefully designed to facilitate the exponential growth in the IoT field. Network slicing is one of the key technologies in the 5G architecture that has the ability to divide the physical network into multiple logical networks (i.e., slices) with different network characteristics. Therefore, network slicing is also a key enabler of realisation of IoT in 5G. Network slicing can satisfy the various networking demands by heterogeneous IoT applications via dedicated slices. In this survey, we present a comprehensive analysis of the exploitation of network slicing in IoT realisation. We discuss network slicing utilisation in different IoT application scenarios, along with the technical challenges that can be solved via network slicing. Furthermore, integration challenges and open research problems related to the network slicing in the IoT realisation are also discussed in this paper. Finally, we discuss the role of other emerging technologies and concepts, such as blockchain and Artificial Intelligence/Machine Learning (AI/ML) in network slicing and IoT integration.

With the advent of 5G era, network slicing has received a great deal of attention as a means to support a variety of wireless services in a flexible manner. Network slicing is a technique to divide a single physical resource network into multiple slices supporting independent services. In beyond 5G (B5G) systems, the main goal of network slicing is to assign the physical resource blocks (RBs) such that the quality of service (QoS) requirements of eMBB, URLLC, and mMTC services are satisfied. Since the goal of each service category is dearly distinct and the computational burden caused by the increased number of time slots is huge, it is in general very difficult to assign RB properly. In this paper, we propose a deep reinforcement learning (DRL)-based network slicing technique to find out the resource allocation policy maximizing the long-term throughput while satisfying the QoS requirements in the B5G systems. Key ingredient of the proposed technique is to reduce the action space by eliminating undesirable actions that cannot satisfy the QoS requirements. Numerical results demonstrate that the proposed technique is effective in maximizing the long-term throughput and handling the coexistence of use cases in the B5G environments.