Efficient multiplexing of ultra-reliable and low-latency communications (URLLC) and enhanced mobile broadband (eMBB) traffic, as well as ensuring the various reliability requirements of these traffic types in 5G wireless communications, is becoming increasingly important, particularly for vertical services. Interference management techniques, such as coordinated inter-cell scheduling, can enhance reliability in dense cell deployments. However, tight inter-cell coordination necessitates frequent information exchange between cells, which limits implementation. This paper introduces a novel RAN slicing framework based on centralized frequency-domain interference control per slice and link adaptation optimized for URLLC. The proposed framework does not require tight inter-cell coordination but can fulfill the requirements of both the decoding error probability and the delay violation probability of each packet flow. These controls are based on a power-law estimation of the lower tail distribution of a measured data set with a smaller number of discrete samples. As design guidelines, we derived a theoretical minimum radio resource size of a slice to guarantee the delay violation probability requirement. Simulation results demonstrate that the proposed RAN slicing framework can achieve the reliability targets of the URLLC slice while improving the spectrum efficiency of the eMBB slice in a well-balanced manner compared to other evaluated benchmarks.

Through the concept of network slicing, a single physical network infrastructure can be split into multiple logically-independent Network Slices (NS), each of which is customized for the needs of its respective individual user or industrial vertical. In the beyond 5G (B5G) system, this customization can be done for many targeted services, including, but not limited to, 5G use cases and beyond 5G. The network slices should be optimized and customized to stitch a suitable environment for targeted industrial services and verticals. This paper proposes a novel Quality of Service (QoS) framework that optimizes and customizes the network slices to ensure the service level agreement (SLA) in terms of end-to-end reliability, delay, and bandwidth communication. The proposed framework makes use of network softwarization technologies, including software-defined networking (SDN) and network function virtualization (NFV), to preserve the SLA and ensure elasticity in managing the NS. This paper also mathematically models the end-to-end network by considering three parts: radio access network (RAN), transport network (TN), and core network (CN). The network is modeled in an abstract manner based on these three parts. Finally, we develop a prototype system to implement these algorithms using the open network operating system (ONOS) as a SDN controller. Simulations are conducted using the Mininet simulator. The results show that our QoS framework and the proposed resource allocation algorithms can effectively schedule network resources for various NS types and provide reliable E2E QoS services to end-users.

Leveraging on Network Function Virtualization (NFV) and Software Defined Networking (SDN), network slicing (NS) is recognized as a key technology that enables the 5G Infrastructure Provider (InP) to support diversified vertical services over a shared common physical infrastructure. 5G end-to-end (E2E) NS is a logical virtual network that spans across the 5G network. Existing works on improving the reliability of the 5G mainly focus on reliable wireless communications, on the other hand, the reliability of an NS also refers to the ability of the NS system to provide continued service. Hence, in this work, we focus on enhancing the reliability of the NS to cope with physical network node failures, and we investigate the NS deployment problem to improve the reliability of the system represented by the NS. The reliability of an NS is enhanced by two means: firstly, by considering the topology information of an NS, critical virtual nodes are backed up to allow failure recovery; secondly, the embedding of the augmented NS virtual network is optimized for failure avoidance. We formulate the embedding of the augmented virtual network (AVN) to maximize the survivability of the NS system as the survivable AVN embedding (S-AVNE) problem through an Integer Linear Program (ILP) formulation. Due to the complexity of the problem, a heuristic algorithm is introduced. Finally, we conduct intensive simulations to evaluate the performance of our algorithm with regard to improving the reliability of the NS system.

Network Slicing (NS) is recognized as a key technology for the 5G network in providing tailored network services towards various types of verticals over a shared physical infrastructure. It offers the flexibility of on-demand provisioning of diverse services based on tenants' requirements in a dynamic environment. In this work, we focus on two important issues related to 5G Core slices: the deployment and the reconfiguration of 5G Core NSs. Firstly, for slice deployment, balancing the workloads of the underlying network is beneficial in mitigating resource fragmentation for accommodating the future unknown network slice requests. In this vein, we formulate a load-balancing oriented 5G Core NS deployment problem through an Integer Linear Program (ILP) formulation. Further, for slice reconfiguration, we propose a reactive strategy to accommodate a rejected NS request by reorganizing the already-deployed NSs. Typically, the NS deployment algorithm is reutilized with slacked physical resources to find out the congested part of the network, due to which the NS is rejected. Then, these congested physical nodes and links are reconfigured by migrating virtual network functions and virtual links, to re-balance the utilization of the whole physical network. To evaluate the performance of deployment and reconfiguration algorithms we proposed, extensive simulations have been conducted. The results show that our deployment algorithm performs better in resource balancing, hence achieves higher acceptance ratio by comparing to existing works. Moreover, our reconfiguration algorithm improves resource utilization by accommodating more NSs in a dynamic environment.

The need of telecommunications operators to reduce Capital and Operational Expenditures in networks which traffic is continuously growing has made them search for new alternatives to simplify and automate their procedures. Because of the different transport network segments and multiple layers, the deployment of end-to-end services is a complex task. Also, because of the multiple vendor existence, the control plane has not been fully homogenized, making end-to-end connectivity services a manual and slow process, and the allocation of computing resources across the entire network a difficult task. The new massive capacity requested by Data Centers and the new 5G connectivity services will urge for a better solution to orchestrate the transport network and the distributed computing resources. This article presents and demonstrates a Network Slicing solution together with an end-to-end service orchestration for transport networks. The Network Slicing solution permits the co-existence of virtual networks (one per service) over the same physical network to ensure the specific service requirements. The network orchestrator allows automated end-to-end services across multi-layer multi-domain network segments making use of the standard Transport API (TAPI) data model for both l0 and l2 layers. Both solutions will allow to keep up with beyond 5G services and the higher and faster demand of network and computing resources.

Communications industry will see dramatic changes with the arrival of 5G. 5G is not only about high capacity and ultra-low latency, but also about accommodating Verticals, providing newer flexibility in business development and agility. Network slicing has become an enabler for on-demand accommodation of such Verticals in a mobile network. To support such new features, 3GPP is continuing standardization of a 5G system with all necessary requirements in mind. This paper provides a detailed view of the standards and the technologies that'll make 5G a reality. Specifically, this paper focuses on the new 5G Radio Access Network (RAN), network slicing enabled new 5G Core (5GC) Network, and new management system capable of handling network slicing related management aspect of a mobile network.

In the context of resource isolation for network slicing, this paper introduces two resource allocation methods especially for the radio access network (RAN) part. Both methods can be implemented by slight modification of the ordinary packet scheduling algorithm such as the proportional fairness algorithm, and guarantee resource isolation by limiting the maximum number of resource blocks (RBs) allocated to each slice. Moreover, since both methods flexibly allocate RBs to the entire system bandwidth, there are cases in which the throughput performance is improved compared to when the system bandwidth is divided in a static manner, especially in a frequency selective channel environment. Numerical results show the superiority of these methods to dividing simply the system bandwidth in a static manner, and show the difference between the features of the methods in terms of the throughput performance of each slice.

In this paper, we posit that, in future mobile network, network softwarization will be prevalent, and it becomes important to utilize deep machine learning within network to classify mobile traffic into fine grained slices, by identifying application types and devices so that we can apply Quality-of-Service (QoS) control, mobile edge/multi-access computing, and various network function per application and per device. This paper reports our initial attempt to apply deep machine learning for identifying application types from actual mobile network traffic captured from an MVNO, mobile virtual network operator and to design the system for classifying it to application specific slices.