With software-defined networking (SDN) and network function virtualization (NFV) technologies, network slicing is a promising solution for resource orchestration to achieve quality-of-service (QoS) isolation in customized services in fifth-generation (5G) networks. In this article, we propose a comprehensive network slicing framework for end-to-end (E2E) QoS provisioning, with differentiated resource types in both wireless and wired network domains considered.

End-to-End Quality of Service in 5G Networks: Examining the Effectiveness of a Network Slicing Framework

Given the highly dynamic traffic loads of mobile Internet of Things (IoT) devices and their stringent quality-of-service requirements, i.e., access delay particularly, as well as the heterogeneous infrastructures among IoT networks, it is a nontrivial task to efficiently deploy cloudlets among large number of access points (APs) in IoT networks, especially for the access delay and network reliability, since different placement schemes would produce various network performances. To combat this issue, we are motivated to investigate in details the optimal placement of cloudlets to minimize the average access delay by applying software-defined networking (SDN) techniques to provide flexible and programmable management for cloudlets deployment in IoT networks with considering the complicated queuing process at numerous SDN-based APs. An enumeration-based optimal placement algorithm (EOPA) is first proposed as benchmark. Then we propose a ranking-based near-optimal placement algorithm (RNOPA) which is able to dynamically adapt to mobile IoT devices and their traffic loads, by treating each AP as a single server queue and adopting an efficient ranking mechanism. As corroborated by extensive simulation results, RNOPA reports access delay very close to that of EOPA. Note that RNOPA outperforms the famous ${K}$ -medians clustering algorithm (KMCA) in both of average cloudlet access delay and reliability, while at the cost of a much lower computational complexity than KMCA.

Optimal Placement of Cloudlets for Access Delay Minimization in SDN-Based Internet of Things Networks

Network softwarization is a major paradigm shift, which enables programmable and flexible system operation in challenging use cases. In the fifth-generation (5G) mobile networks, the more advanced scenarios envision transfer of high-rate mission-critical traffic. Achieving end-to-end reliability of these stringent sessions requires support from multiple radio access technologies and calls for dynamic orchestration of resources across both radio access and core network segments. Emerging 5G systems can already offer network slicing, multi-connectivity, and end-to-end quality provisioning mechanisms for critical data transfers within a single software-controlled network. Whereas these individual enablers are already in active development, a holistic perspective on how to construct a unified, service-ready system as well as understand the implications of critical traffic on serving other user sessions is not yet available. Against this background, this paper first introduces a softwarized 5G architecture for end-to-end reliability of the mission-critical traffic. Then, a mathematical framework is contributed to model the process of critical session transfers in a softwarized 5G access network, and the corresponding impact on other user sessions is quantified. Finally, a prototype hardware implementation is completed to investigate the practical effects of supporting mission-critical data in a softwarized 5G core network, as well as substantiate the key system design choices.

Achieving End-to-End Reliability of Mission-Critical Traffic in Softwarized 5G Networks

HTTP adaptive streaming (HAS) is receiving much attention from both industry and academia as it has become the de facto approach to stream media content over the Internet. Recently, we proposed a streaming architecture called SDNDASH  [1] to address HAS scalability issues including video instability, quality of experience (QoE) unfairness, and network resource underutilization, while maximizing per player QoE. While SDNDASH was a significant step forward, there were three unresolved limitations: 1) it did not scale well when the number of HAS players increased; 2) it generated communication overhead; and 3) it did not address client heterogeneity. These limitations could result in suboptimal decisions that led to viewer dissatisfaction. To that effect, we propose an enhanced intelligent streaming architecture, called SDNHAS, which leverages software defined networking (SDN) capabilities of assisting HAS players in making better adaptation decisions. This architecture accommodates large-scale deployments through a cluster-based mechanism, reduces communication overhead between the HAS players and SDN core, and allocates the network resources effectively in the presence of short- and long-term changes in the network.

SDNHAS: An SDN-Enabled Architecture to Optimize QoE in HTTP Adaptive Streaming

The highly demanding Over-The-Top (OTT) multimedia applications pose increased challenges to Internet Service Providers (ISPs) for assuring a reasonable Quality of Experience (QoE) to their customers due to lack of flexibility, agility and scalability in traditional networks. The future networks are shifting towards the cloudification of the network resources via Software Defined Networks (SDN) and Network Function Virtualization (NFV). This will equip ISPs with cutting-edge technologies to provide service customization during service delivery and offer QoE which meets customers’ needs via intelligent QoE control and management approaches. Towards this end, we provide in this paper a tutorial and a comprehensive survey of QoE management solutions in current and future networks. We start with a high-level description of QoE management for multimedia services, which integrates QoE modelling, monitoring, and optimization. This followed by a discussion of HTTP Adaptive Streaming (HAS) solutions as the dominant technique for streaming videos over the best-effort Internet. We then summarize the key elements in SDN/NFV along with an overview of ongoing research projects, standardization activities and use cases related to SDN, NFV, and other emerging applications. We provide a survey of the state-of-the-art of QoE management techniques categorized into three different groups: a) QoE-aware/driven strategies using SDN and/or NFV; b) QoE-aware/driven approaches for adaptive streaming over emerging architectures such as multi-access edge computing, cloud/fog computing, and information-centric networking; and c) extended QoE management approaches in new domains such as immersive augmented and virtual reality, mulsemedia and video gaming applications. Based on the review, we present a list of identified future QoE management challenges regarding emerging multimedia applications, network management and orchestration, network slicing and collaborative service management in softwarized networks. Finally, we provide a discussion on future research directions with a focus on emerging research areas in QoE management, such as QoE-oriented business models, QoE-based big data strategies, and scalability issues in QoE optimization.

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QoE Management of Multimedia Streaming Services in Future Networks: A Tutorial and Survey

The growing demand for online distribution of high quality and high throughput content is dominating today’s Internet infrastructure. This includes both production and user-generated media. Among the myriad of media distribution mechanisms, HTTP adaptive streaming (HAS) is becoming a popular choice for multi-screen and multi-bitrate media services over heterogeneous networks. HAS applications often compete for network resources without any coordination between each other. This leads to quality of experience (QoE) fluctuations on delivered content, and unfairness between end users, while new network protocols, technologies, and architectures, such as software defined networking (SDN), are being developed for the future Internet. The programmability, flexibility, and openness of these emerging developments can greatly assist the distribution of video over the Internet. This is driven by the increasing consumer demands and QoE requirements. This paper introduces a novel user-level fairness model UFair and its hierarchical variant UFair $^{\text {HA}}$ , which orchestrate HAS media streams using emerging network architectures and incorporate three fairness metrics (video quality, switching impact, and cost efficiency) to achieve user-level fairness in video distribution. UFair $^\text {HA}$ has also been implemented in a purpose-built SDN testbed using open technologies, including OpenFlow. Experimental results demonstrate the performance and feasibility of our design for video distribution over future networks.

/pdf/a-scalable-user-fairness-model-for-adaptive-video-streaming-48cr9k6kp7.pdf

A Scalable User Fairness Model for Adaptive Video Streaming Over SDN-Assisted Future Networks

Network services are the key mechanism for operators to introduce intelligence and generate profit from their infrastructures. The growth of the number of network users and the stricter application network requirements have highlighted a number of challenges in orchestrating services using existing production management and configuration protocols and mechanisms. Recent networking paradigms like Software Defined Networking (SDN) and Network Function Virtualization (NFV), provide a set of novel control and management interfaces that enable unprecedented automation, flexibility and openness capabilities in operator infrastructure management. This paper presents Baguette, a novel and open service orchestration framework for operators. Baguette supports a wide range of network technologies, namely optical and wired Ethernet technologies, and allows service providers to automate the deployment and dynamic re-optimization of network services. We present the design of the orchestrator and elaborate on the integration of Baguette with existing low-level network and cloud management frameworks.

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Baguette: Towards End-to-End Service Orchestration in Heterogeneous Networks

SDQ: Enabling rapid QoE experimentation using Software Defined Networking

BGP has long been the de-facto control plane protocol for inter-network connectivity. Although initially designed to provide best-effort routing between ASes, the evolution of Internet services has created a demand for more complex control functionalities using the protocol. At the heart of this challenge lies the static nature of configuration mechanisms and the limited programmability of existing BGP speakers. Meanwhile, the SDN paradigm has demonstrated that open and generic network control APIs can greatly improve network functionality and seamlessly enable greater flexibility in network management. In this paper, we argue that BGP speaking systems can and should provide an open and rich control and configuration mechanism, in order to address modern era network control requirements. Towards this goal, we present λBGP, a modular and extensible BGP framework written in Haskell. The framework offers an extensible integration model for reactive BGP control that remains backward compatible with existing BGP standards and allows network managers to define route processing policies using a high-level language and to dynamically inject information sources into the path selection logic. Using a high-performance BGP traffic generator, we demonstrate that λBGP offers performance comparable to production BGP speakers, while dynamic AS route processing policies can be written in just a few lines of code.

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Nicholas Hart

Papers

A Scalable User Fairness Model for Adaptive Video Streaming Over SDN-Assisted Future Networks

Baguette: Towards End-to-End Service Orchestration in Heterogeneous Networks

SDQ: Enabling rapid QoE experimentation using Software Defined Networking

λBGP: Rethinking BGP programmability