A joint utility optimization based virtual AP and network slice selection scheme for SDWNs

Rarely the interest in a new networking paradigm has increased at such a velocity as it is happening for software defined networking (SDN). Motivations of this hype of interest are several but the most important can be re-conducted to the following three: (i) SDN simplifies network configuration and management; (ii) SDN makes the network evolvable; (iii) SDN frees operators from vendors' lock-in. Eagerly, in some cases, or reluctantly, in others, both operators and manufacturers of communication and networking equipments have started new lines of research, development, and marketing focused on SDN. A quick look at the list of members of the organizations promoting the development of SDN-related standards suffices to understand that players of the wireless domain are trying to ride this wave as well. However, it is difficult for the observers to understand where such a wave is headed to in very common networking scenarios involving infrastructureless wireless communications. This paper is an attempt to fill this gap. In fact, a major objective of this paper is to analyze (i) what are the advantages of SDN in infrastructureless wireless networking environments such as wireless personal area networks (W-PANs), and (ii) what are the requirements that must be satisfied to apply SDN in W-PANs. Furthermore, a complete SDN solution for W-PANs, named Software Defined Wireless Network (SDWN), is introduced and a prototype implementation is described.

Innovative technologies, such as Software-Defined Networking (SDN) and Network Functions Virtualization (NFV), are enabling the possibility of managing network infrastructures and their services for enhancing network flexibility, efficient resource control, and cost-efficiency. How to combine these technologies requires taking into account the requirements established by the scenarios being executed, which can change at any time due to their dynamism. Network Slicing appeared to this end. This new technique tailors the needs of a particular scenario whose requirements are extremely heterogeneous and complex. By using Network Slicing, SDN/NFV-enabled environments can be strengthened to manage network resources and services depending on those requirements. Nevertheless, Network Slicing approaches lack management mechanisms that consider the heterogeneity and dynamism provided by scenarios based on future mobile networks. This article presents a formal definition of the Network Slicing information model, where all elements interacting with the Network Slices life cycle are formally represented. Another important contribution is a mobility-aware architecture that combines NFV/SDN techniques and introduces innovative components responsible for managing and orchestrating the Network Slices. Finally, a systematic comparison is made between the existing architectures and the proposed one.

Looking forward to the not-so-far future, wireless networks will comprise centralised processing, mixed macro and small cells deployments as well as new radio technologies in order to support very high data rates and traffic types that are characterised by connectionless and sporadic transmission of short packets such as those employed by machine to machine communication devices. In current radio access networks, there is a very clear difference between the fronthaul and backhaul. In comparison with the advent of centralised radio access networks, the difference between the fronthaul and backhaul networks has been shifted further away from the user. Subsequently, in the latest propositions for 5G architectures, they are being merged into an `xhaul' (crosshaul) network where the fronthaul and backhaul concepts no longer exist. In particular instead of using a dedicated centralised processing pool for a set of cellular access points, the idea of using centralised processing within the core network has emerged. With the use of network function virtualisation and centralised processing in data centres, cloud-RANs can be used to provide access to the distribution antenna, removing the need for backhauling and fronthauling. The cloud-RAN can perform the duties of the Mobility Management Entity and Serving Gateway and at the same time can also process each cellular access point's analogue processing using a flexible virtualised software environment. Assuming this is used along with split processing, what needs also to be addressed is the means of communication between the cloudRAN and the distribution antenna. Traditional solutions such as the common public radio interface might not be sufficient to meet all requirements. Largely, Ethernet is being proposed. When Ethernet is used, software-defined networking (SDN) can also be used to dynamically control data flows to and from the cloud-RAN, as well as providing additional benefits, such as network slicing, allowing multiple cellular operators to use the same xhaul infrastructure. This chapter, therefore, largely elaborates on xhaul networks by investigating the potential of SDN to provide an effective user experience for the services provided. The control of specific services such as billing, roaming and registration could then be sent via alternative links such as satellite links, as latency for these packets are not critical, resulting in reduced packet delay on the data plane. It is apparent that for Gbps wireless connectivity, targeted by 5G, the data rate requirements on the centralised cloud xhaul link will be in the range of several Gbps with a latency requirement close to 1 ms.

The rapid development of smart grid has put forward higher requirements on communication technology. With the rapid development of power wireless communication network, the demand of power business becomes more and more complicated and diverse. However, the current single-standard network has poor coverage, poor power service carrying capacity, and weak transmission stability and security. To address the above problems, this paper explores the network slicing technology for intelligent power distribution services. Based on the analysis of existing network access selection methods, a network selection strategy for quality of service (QoS) assurance of power services is proposed for the characteristics of power distribution services. Combining its own QoS requirements and the characteristics of the network to be accessed, the power service can realize the access selection of the optimal adaptation network. In order to better meet various vertical industry applications, network slicing is required in both the core network and the radio access network, i.e., end-to-end network slicing is realized, and network slicing can be customized to tailor network functions and reasonably allocate network resources according to service scenario requirements. After receiving a request for network slicing, operators need to map the virtual network functions required for network slicing to the underlying physical network, a process that involves the optimal allocation of physical resources.

Network slicing is one of the most promising enabling technologies for next generation mobile network (5G), which spans over all domains of the network, including data centers, core networks (CNs), transport networks, and radio access networks (RANs). As such wide range of technologies are involved, it is difficult to ensure an end-to-end (network) slice working stably all the time. First, for both CN and RAN slices, bugs may accidentally occur in virtual network functions(VNFs), which can invalidate the slice and trigger a recovery process. In addition, the traffic demands to be accommodated by a CN or RAN slice can be stochastic rather than deterministic parameters, and changes of traffic demands that are too drastic may trigger slice reconfiguration. In this chapter, we investigate a robust RAN slicing mechanism to address slice recovery and reconfiguration in a unified framework. A slice is constituted by a set of VNFs and links and remapping is a process of re-selecting VNFs and links to recover failures. As a baseline, we first formulate a recovery problem to solve remapping of a slice with deterministic traffic demands. Based on that, we propose two robust RAN slicing algorithms for slice recovery under stochastic demands. Numerical results reveal that the proposed robust RAN slicing algorithms can provide adjustable tolerance of traffic uncertainties, compared with the baseline algorithm. In addition, the tradeoff between the robustness of slices and the average load of links and the tradeoff between the robustness and the average recovery time of slices can be efficiently managed and controlled.

Network slicing is one of the key enabling techniques for 5G, allowing Mobile Network Operators (MNOs) to support services with diverging requirements on top of their infrastructure. The MNOs should be able to offer network slices as a service and provide customisable and independent virtual networks to verticals. The slicing of an end-to-end (E2E) mobile network is divided into Core Network (CN) slicing, and Radio Access Network (RAN) slicing. In this paper, we assess the requirements for using radio hypervisors to enable RAN as a Service (RANaaS). We evaluate the current state-of-the-art on radio virtualisation with respect to these requirements and identify the missing features. Then, we present the eXtensible Virtualisation Layer (XVL), a software layer that provides the missing functionality for enabling RANaaS and can be added on top of existing radio hypervisors. We outline XVL's architecture and design choices, as well as evaluate its performance in terms of the delay to provision virtual radios, the delay introduced to forward IQ samples, and the computational overhead. Our results show that XVL enables leveraging existing radio hypervisors to support RANaaS.

In this chapter, we present a comprehensive end-to-end (E2E) network slicing framework for fifth-generation (5G) wireless and core networks and provide our vision on network slicing for beyond 5G (B5G) networks using artificial intelligence (AI) technologies. We first give an introduction on the 5G communication networks by specifying distinct 5G networking characteristics. As the key features of 5G pose challenges on quality-of-service (QoS)-oriented resource provisioning, a new concept of network slicing is presented, based on software-defined networking (SDN) and network function virtualization (NFV) technologies, to enhance the overall resource utilization while guaranteeing QoS isolation among services. We focus on developing specific network slicing solutions for both 5G wireless networks and core networks. In addition, the evolution of B5G networks is discussed in terms of a potential networking paradigm shift with new service key performance indicators (KPIs). To satisfy B5G service requirements, a framework of AI-assisted network slicing lifecycle is developed to automate the slice creation with reduced slice management complexity. A case study is presented to demonstrate the effectiveness of the proposed E2E network slicing solutions.Keywords5G communication networksNetwork slicingWireless networksRadio resource slicingCore networksComputing and transmission resource slicingBeyond 5G networksAI-assisted network slicingQoSE2E delay

5G research has been looking for flexible, dynamic and low-latency network architectures. In this regard, Software-Defined Networking (SDN) and Network Functions Virtualization (NFV) have been key enablers for the next generation networks. Although SDN was originally designed for wired networks, such as data-centre networks, its popularity in the research community has extended its boundaries, also becoming considered for wireless networks. With its flexibility and programmability, Software-Defined Wireless Networks (SDWN) have been suggested for mobile networks evolution. This chapter provides an overview of how virtualization of network entities (such as points of attachment and flow-based mobility management entities) can contribute to a new level of abstraction in heterogeneous wireless access environments. To assess the enhancement potential of such mechanisms, a framework case study is presented and evaluated, showcasing flow-based mobility scenarios in multi-technology environments.


 Over the last decade, wireless devices have developed rapidly until predictions will develop with high complexity and dynamic. So that new capabilities are needed for wireless problems in this problem. Software Defined Network (SDN) is generally a wire-based network, but to meet the needs of users in terms of its implementation, it has begun to introduce a Wireless-based SDN called Software Defined Wireless Network (SDWN) which provides good service quality and reach and higher tools, so as to be able to provide new capabilities to wireless in a high complexity and very dynamic. When SDN is implemented in a wireless network it will require a routing solution that chooses paths due to network complexity. In this paper, SDWN is tested by being applied to mesh topologies of 4,6 and 8 access points (AP) because this topology is very often used in wireless-based networks. To improve network performance, Dijkstra's algorithm is added with the user mobility scheme used is RandomDirection. The Dijkstra algorithm was chosen because it is very effective compared to other algorithms. The performance measured in this study is Quality of Service (QoS), which is a parameter that indicates the quality of data packets in a network. The measurement results obtained show that the QoS value in this study meets the parameters considered by the ITU-T G1010 with a delay value of 1.3 ms for data services and packet loss below 0.1%. When compared with the ITU-T standard, the delay and packet loss fall into the very good category.

In 5G networks, the deployment of network slices enabled by Software-Defined Networking (SDN) is becoming a critical component for delivering tailored services to meet diverse application needs. However, this introduces challenges in network management, particularly in efficiently allocating resources to ensure that each network slice meets its specific Quality of Service (QoS) and availability requirements. Simultaneously, it must optimize overall network performance and network operator’s profit, which is linked to the Quality of Experience (QoE) of the end-users. Existing works offer either an availability-based solution or a QoE-aware solution to this problem, but not both. This paper addresses the end-to-end network slice resource allocation problem by simultaneously considering QoS and availability requirements in slice placement, while employing a QoE-aware strategy for resource allocation. We propose a framework that optimizes the network operator profit i.e. the highest QoE with the least resource usage, and can be flexibly configured to model realistic scenarios. Arbitrary network slice requirements can be defined using slice-specific QoS/QoE mapping, resource requirements, end-to-end latency and availability. For solving the formulated problem a Mixed Integer Nonlinear Programming (MINLP) formulation and efficient heuristic methods are proposed. Our solution accounts for the non-linear QoS/QoE relationship, utilizes redundantly placed Service Function Chains (SFCs) to increase availability, and supports the sharing of Virtual Network Functions (VNFs) among SFCs to optimize resource usage. Through extensive simulations on realistic network topologies and slice requests, we demonstrate the framework’s effectiveness in offering flexible and efficient network slice placement and resource allocation, utilizing a baseline heuristic from related studies. The results indicate that while the exact method delivers an optimal solution, heuristic approaches are suitable for time-sensitive tasks, such as dynamic slice configuration.

Network slicing is a fundamental feature of 5G systems that facilitates the provision of particular system behaviours adapted to specific service/application domains on top of a common network infrastructure. A network slice is in general composed by a core network slice and a Radio Access Network (RAN) slice. The realization of RAN slices is particularly challenging because it requires configuring and operating traffic differentiation and protection mechanisms to simultaneously deliver multiple and diverse RAN behaviors over a given pool of radio resources. In this context, this paper proposes to characterize the behavior of a RAN slice through the specification of a set of control parameters that are used to dictate the operation of the packet scheduling function at Layer 2 and the radio admission control function at Layer 3. An evaluation of the suitability of these parameters for achieving efficient radio resource sharing and isolation between RAN slices is presented when configuring a network for supporting a slice with multiple enhanced Mobile BroadBand services and another slice for providing Mission Critical services. The analysis reveals the different impact of the Layer 3 and Layer 2 parameters for isolating services of different slices depending on whether they require guaranteed or non-guaranteed bit rates.

The rise of 5G mobile network and the increasing of the number of connected devices with the deployment of new technologies, make the operator thinking of using new network architecture to meet the requirement of such situation. Cloud Radio Access Network (C-RAN) is a network that become the infrastructure of next generation, with the new evolving technologies, such as Network Function Virtualization (NFV) and Software Defined Networking (SDN). Network slicing enables the orchestration of Radio Access Network (RAN) resources, by isolating the physical network to virtual slices each of them reserved for determined application or services. Besides, implementing optimization method on C-RAN infrastructure led to a large number of profit chances. This paper will explain in depth the importance of such technologies and methods in Virtualized C-RAN.

An accelerated Benders decomposition approach for virtual base station formation in stochastic Cloud-RANs

5G networks represent a paradigm shift from their 4G predecessors, engineered to cater to the burgeoning demands of densely populated areas and the high data throughput requirements of the Internet of Things (IoT) and smart city infrastructures. Beyond enhancing fundamental network attributes such as reliability, availability, and security, 5G introduces architectural innovations to accommodate these advanced needs. This paper delves into the architectural nuances of 5G, focusing primarily on the Standalone (SA) deployment method, distinguished by its utilization of network slicing. This approach leverages cutting-edge virtual network technologies, including Software-Defined Networking (SDN) and Network Function Virtualization (NFV), to forge virtual network slices tailored to diverse consumer needs. Such customization is imperative for meeting the expansive and varied connectivity demands characteristic of 5G networks.To navigate the complexities of 5G architecture, this study advocates for the adoption of Reference Architectures (RAs), which provide a high-level abstraction framework for dissecting and understanding intricate systems. By proposing a model that outlines the standalone architecture of 5G networks, our research lays the groundwork for evolving this model into a comprehensive RA for 5G. This foundational work is instrumental in equipping system designers with the tools necessary for generalizing systems to manage design and deployment challenges effectively, as well as the heterogeneity inherent in system components. Additionally, our proposed model facilitates the establishment of a common vocabulary, promoting a coherent understanding of component interactions and offering a unified system perspective. Ultimately, this paper contributes a pivotal model that not only enhances our comprehension of 5G network architecture but also paves the way for future advancements in network design and deployment, promising to significantly impact the development of smart cities and IoT ecosystems.Keywords: 5G, 5G architecture, Reference architecture, patterns. Network slicing, Network Function Virtualization, Virtual Network Function.

The fifth-generation mobile network presents a wide range of services which have different requirements in terms of performance, bandwidth, reliability, and latency. The legacy networks are not capable to handle these diverse services with the same physical infrastructure. In this way, network virtualization presents a reliable solution named network slicing that supports service heterogeneity and provides differentiated resources to each service. Network slicing enables network operators to create multiple logical networks over a common physical infrastructure. In this research article, we have designed and implemented an intent-based network slicing system that can slice and manage the core network and radio access network (RAN) resources efficiently. It is an automated system, where users just need to provide higher-level network configurations in the form of intents/contracts for a network slice, and in return, our system deploys and configures the requested resources accordingly. Further, our system grants the automation of the network configurations process and reduces the manual effort. It has an intent-based networking (IBN) tool which can control, manage, and monitor the network slice resources properly. Moreover, a deep learning model, the generative adversarial neural network (GAN), has been used for the management of network resources. Several tests have been carried out with our system by creating three slices, which shows better performance in terms of bandwidth and latency.