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Scalable QoE-aware Path Selection in SDN-based Mobile Networks
Abstract and Figures
To deal with the massive traffic produced by video applications, mobile operators rely on offloading technologies such as Small Cells, Content Delivery Networks and, shortly, Cloud Edge and 5G Device to Device communications. Although these techniques are fundamental for improving network efficiency , they produce a multitude of paths onto which the user traffic can be forwarded. Thus, a critical problem arises about how to handle the increasing video traffic while managing the interplay between infrastructure optimization and the user's Quality of Experience (QoE). Solving this problem is remarkably difficult, and recent investigations do not consider the large-scale context of mobile operator networks. To address this issue, we present a novel QoE-aware path deployment scheme for large-scale SDN-based mobile networks. The scheme relies on both a polynomial-time algorithm for composing multiple QoS metrics and a scalable QoS to QoE translation strategy. Considering real mobile operator network and video traffic traces, we show that the proposed algorithm outperformed state-of-the-art approaches by reducing impaired videos in aggregate MOS by at least 37% and lowering accumulated video stall length four times.
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With the increasing traffic of vod, network providers are seeking to deliver high qoe for their users. Many methods have been proposed to assess vod-related qoe. Some of them rely on client instrumentation and reporting qoe information to network elements, such as Server and Network Assisted DASH, others are based on statistical methods that make qoe inferences using monitored network conditions, such as throughput and delays. In this article, we present a practical method to estimate qoe for vod using the widely supported icmp probes. Measured network conditions are used as input to a ml model that estimates qoe in terms of mos, based on the ITU-T P.1203 Recommendation. The estimation encompasses video quality switches and playback stalls. We estimate mos with an average rmse of 1.05 for a catalog of 25 different videos, training a model with sessions of the shortest video, and evaluating the generalization to the full catalog. We performed experiments using a virtualized setup as well as in a Wide Area Network.
The highly demanding Over-The-Top (OTT) multi-media 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 scal-ability 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.
We investigate a quality of experience (QoE) based computation offloading scheduling problem for Edge Computing, in which data processing and decision making are placed at the edge of the Internet and close to smart mobile devices and end users. Considering that smart device owners value both response time and battery life, it is reasonable to properly address the latency and energy tradeoff. This paper captures a user-centric view to tackle the offloading scheduling problem via jointly allocating communication and computation resources with consideration of the QoE of users. We formulate our design as a mix-integer non-linear programming (MINLP) problem and solve it in an efficient way by RLT-based branch-and-bound method. Numerical results demonstrate that the proposed offloading scheme achieves an improved performance on latency time and energy consumption, when compared to benchmark schemes.
In software defined networking (SDN), flow migration will be required when topology changes to improve network performance such as load balancing. However, black holes, loops and transient congestion may occur during flow migration due to the asynchronous update of switches on the data plane. Therefore, in this paper, we propose a novel segmented update method to shorten the time of rules update, and a novel transient congestion avoidance algorithm to minimize the number of delayed updating flows, which can both reduce update time of flows. Specifically, we construct three novel models to guarantee no black holes, no loops and no transient congestion, respectively. The first two models to avoid black holes and loops can update multiple nodes in each segment instead of updating the nodes one by one like Cupid. The third model to avoid transient congestion minimizes the number of delayed updating flows. Subsequently, three novel black holes avoidance algorithm, loops avoidance algorithm and congestion avoidance algorithm are respectively proposed. Furthermore, we propose a novel rules update (RU) algorithm which combines these three algorithms to update the rules to avoid black holes, loops and transient congestion simultaneously. Simulation results show that our scheme can increase the number of directly updated flows by 75% on a single congestion link and reduce the rules update time of the flows by 34% compared with the existing work.
Nowadays, there is a fast-paced shift from legacy telecommunication systems to novel Software Defined Network (SDN) architectures that can support on-the-fly network reconfiguration, therefore, empowering advanced traffic engineering mechanisms. Despite this momentum, migration to SDN cannot be realized at once especially in high-end cost networks of Internet Service Providers (ISPs). It is expected that ISPs will gradually upgrade their networks to SDN over a period that spans several years. In this paper, we study the SDN upgrading problem in an ISP network: which nodes to upgrade and when. We consider a general model that captures different migration costs and network topologies, and two plausible ISP objectives; first, the maximization of the traffic that traverses at least one SDN node, and second, the maximization of the number of dynamically selectable routing paths enabled by SDN nodes. We leverage the theory of submodular and supermodular functions to devise algorithms with provable approximation ratios for each objective. Using real-world network topologies and traffic matrices, we evaluate the performance of our algorithms and show up to 54% gains over state-of-the-art methods. Moreover, we describe the interplay between the two objectives; maximizing one may cause a factor of 2 loss to the other.
The provisioning of the quality to end users is a major objective for the successful deployment of multimedia services over the Internet. It is more and more evident from past research and service deployments that such an objective often requires a collaboration among the different parties that are involved in the delivery of the service. This paper specifically focuses on the cooperation between the Over-The-Top (OTTs) and the Internet Service Providers (ISPs) and propose a novel service delivery approach that is purely driven by the Quality of Experience (QoE) provided to the final common users. Initially, we identify the need of the collaboration among the OTTs and the ISPs where we not only highlight some of the enterprise level motivations (revenue generation) but also the technical aspects which require collaboration. Later, we provide a reference architecture with the required modules and vertical interfaces for the interaction among the OTTs and the ISPs. Then, we provide a collaboration model where we focus on the modeling of the revenue, whose maximization drives the collaboration. The revenue is considered to be dependent on the user churn, which in turn is affected by the QoE and is modeled using the Sigmoid function. We illustrate simulation results based on our proposed collaboration approach which highlight how the proposed strategy increases the revenue generation and QoE for the OTTs and the ISPs hence providing a ground for ISP to join the loop of revenue generation between OTTs and users.
Adaptive streaming dynamically adapts video quality level according to the perceived device status and network conditions. It requires several representations of the same content, each encoded at different quality rates. As a representative example, H.264/SVC eliminates the requirement of redundant representations, improving the efficiency of caching and storage infrastructure. SVC video consists of a "Base Layer" and one or more of "Enhancement Layers". These layers have inter-dependencies and different QoS requirements. On another side, SDN allows forwarding tables to be adjusted dynamically, enabling us to route every individual flow differently. In this paper, we propose ELBA, an algorithm for scalable video streaming over SDN. ELBA utilizes the dynamic re-routing capability of SDN, to stream different layers of SVC coded video over possibly different suitable paths. In the proposed video streaming system, we use a novel mechanism to exchange information between the control plane and streaming servers. We have compared the performance of our approach with traditional Internet routing technique. Our evaluation results show that our proposal is not only feasible but in particular, it significantly outperforms the traditional Internet routing approach in terms of QoE.
Traditional routing in the Internet is best-effort which makes it challenging for video streaming since no throughput, jitter, delay or loss rate is guaranteed. As different paths have different characteristics, path differentiation such as multipath routing is a promising technique to be used for meeting QoS requirements of media-intensive applications. Using overlay networks different paths are offered which enable more flexibility in QoS and congestion control while the reliability of the connections is enhanced.
Software Defined Networking (SDN) is known to be a promising solution to the problems of routing as it provides fine-grained control over packet handling. Relying on SDN, we propose an adaptive multipath provisioning scheme ensuring maximal bandwidth and resiliency of media transfer in overlay networks. The scheme is a time slot-based approach which dynamically finds multipaths. It relies on both active probing and traffic prediction.
The experimental results confirm that a more accurate prediction together with more frequent probing lead to fewer number of path re-calculation and also indicate that the proposed scheme enhances the reliability of connections while a more balanced load is achieved in the network compared to the shortest path-based scheme.
