Enabling virtual radio functions on software defined radio for future wireless networks

Today's wired networks have become highly flexible, thanks to the fact that an increasing number of functionalities are realized by software rather than dedicated hardware. This trend is still in its early stages for wireless networks, but it has the potential to improve the network's flexibility and resource utilization regarding both the abundant computational resources and the scarce radio spectrum resources. In this work we provide an overview of the enabling technologies for network reconfiguration, such as Network Function Virtualization, Software Defined Networking, and Software Defined Radio. We review frequently used terminology such as softwarization, virtualization, and orchestration, and how these concepts apply to wireless networks. We introduce the concept of Virtual Radio Function, and illustrate how softwarized/virtualized radio functions can be placed and initialized at runtime, allowing radio access technologies and spectrum allocation schemes to be formed dynamically. Finally we focus on embedded Software-Defined Radio as an end device, and illustrate how to realize the placement, initialization and configuration of virtual radio functions on such kind of devices

A service-oriented hybrid access network and clouds architecture

Many telecom operators are deploying their own cloud infrastructure with the two-fold objective of providing cloud services to their customers and enabling network function virtualization. In this article we present an architecture we call SHINE, which focuses on orchestrating cloud with heterogeneous access and core networks. In this architecture intra and inter DC connectivity is dynamically controlled, maximizing the overall performance in terms of throughput and latency while minimizing total costs. The main building blocks are: a future-proof network architecture that can scale to offer potentially unlimited bandwidth based on an active remote node (ARN) to interface end-users and the core network; an innovative distributed DC architecture consisting of micro-DCs placed in selected core locations to accelerate content delivery, reducing core network traffic, and ensuring very low latency; and dynamic orchestration of the distributed DC and access and core network segments. SHINE will provide unprecedented quality of experience, greatly reducing costs by coordinating network and cloud and facilitating service chaining by virtualizing network functions.Peer ReviewedPostprint (author’s final draft

Network Function Virtualization in Dynamic Networks: A Stochastic Perspective

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordAs a key enabling technology for 5G network softwarization, Network Function Virtualization (NFV) provides an efficient paradigm to optimize network resource utility for the benefits of both network providers and users. However, the inherent network dynamics and uncertainties from 5G infrastructure, resources and applications are slowing down the further adoption of NFV in many emerging networking applications. Motivated by this, in this paper, we investigate the issues of network utility degradation when implementing NFV in dynamic networks, and design a proactive NFV solution from a fully stochastic perspective. Unlike existing deterministic NFV solutions, which assume given network capacities and/or static service quality demands, this paper explicitly integrates the knowledge of influential network variations into a twostage stochastic resource utilization model. By exploiting the hierarchical decision structures in this problem, a distributed computing framework with two-level decomposition is designed to facilitate a distributed implementation of the proposed model in large-scale networks. The experimental results demonstrate that the proposed solution not only improves 3∼5 folds of network performance, but also effectively reduces the risk of service quality violation.The work of Xiangle Cheng is partially supported by the China Scholarship Council for the study at the University of Exeter. This work is also partially supported by the UK EPSRC project (Grant No.: EP/R030863/1)

Identifying 5G system enhancements: enabling technologies for multi-service networks

Proceeding of: 2018 IEEE Conference on Standards for Communications and Networking (CSCN)The fifth generation (5G) of mobile and wireless communications networks aims at addressing a diverse set of use cases, services, and applications with a particular focus on enabling new business cases via network slicing. The development of 5G has thus advanced quickly with research projects and standardization efforts resulting in the 5G baseline architecture. Nevertheless, for the realization of native end-to-end (E2E) network slicing, further features and optimizations shall still be introduced. In this paper, we provide a gap analysis of current 5G system (5GS) with respect to some specific enhancements and detail our insights on the enabling innovations that can fill the identified gaps. We will then discuss the essential building blocks and design principles of an evolved 5G baseline architecture capitalizing on the innovations that are being developed.This work has been performed in the framework of the H2020 project 5G-MoNArch co-funded by the EU

Framework for Virtualized Network Functions (VNFs) in Cloud of Things Based on Network Traffic Services

The cloud of things (CoT), which combines the Internet of Things (IoT) and cloud computing, may offer Virtualized Network Functions (VNFs) for IoT devices on a dynamic basis based on service-specific requirements. Although the provisioning of VNFs in CoT is described as an online decision-making problem, most widely used techniques primarily focus on defining the environment using simple models in order to discover the optimum solution. This leads to inefficient and coarse-grained provisioning since the Quality of Service (QoS) requirements for different types of CoT services are not considered, and important historical experience on how to provide for the best long-term benefits is disregarded. This paper suggests a methodology for providing VNFs intelligently in order to schedule adaptive CoT resources in line with the detection of traffic from diverse network services. The system makes decisions based on Deep Reinforcement Learning (DRL) based models that take into account the complexity of network configurations and traffic changes. To obtain stable performance in this model, a special surrogate objective function and a policy gradient DRL method known as Policy Optimisation using Kronecker-Factored Trust Region (POKTR) are utilised. The assertion that our strategy improves CoT QoS through real-time VNF provisioning is supported by experimental results. The POKTR algorithm-based DRL-based model maximises throughput while minimising network congestion compared to earlier DRL algorithms

Availability-driven NFV orchestration

Virtual Network Functions as a Service (VNFaaS) is a promising business whose technical directions consist of providing network functions as a Service instead of delivering standalone network appliances, leveraging a virtualized environment named NFV Infrastructure (NFVI) to provide higher scalability and reduce maintenance costs. Operating the NFVI under stringent availability guarantees is fundamental to ensure the proper functioning of the VNFaaS against software attacks and failures, as well as common physical device failures. Indeed the availability of a VNFaaS relies on the failure rate of its single components, namely the physical servers, the hypervisor, the VNF software, and the communication network. In this paper, we propose a versatile orchestration model able to integrate an elastic VNF protection strategy with the goal to maximize the availability of an NFVI system serving multiple VNF demands. The elasticity derives from (i) the ability to use VNF protection only if needed, or (ii) to pass from dedicated protection scheme to shared VNF protection scheme when needed for a subset of the VNFs, (iii) to integrate traffic split and load-balancing as well as mastership role election in the orchestration decision, (iv) to adjust the placement of VNF masters and slaves based on the availability of the different system and network components involved. We propose a VNF orchestration algorithm based on Variable Neighboring Search, able to integrate both protection schemes in a scalable way and capable to scale, while outperforming standard online policies