Cumulative Quality Modeling for HTTP Adaptive Streaming

Thanks to the abundance of Web platforms and broadband connections, HTTP Adaptive Streaming has become the de facto choice for multimedia delivery nowadays. However, the visual quality of adaptive video streaming may fluctuate strongly during a session due to bandwidth fluctuations. So, it is important to evaluate the quality of a streaming session over time. In this paper, we propose a model to estimate the cumulative quality for HTTP Adaptive Streaming. In the model, a sliding window of video segments is employed as the basic building block. Through statistical analysis using a subjective dataset, we identify three important components of the cumulative quality model, namely the minimum window quality, the last window quality, and the average window quality. Experiment results show that the proposed model achieves high prediction performance and outperforms related quality models. In addition, another advantage of the proposed model is its simplicity and effectiveness for deployment in real-time estimation. The source code of the proposed model has been made available to the public at https://github.com/TranHuyen1191/CQM

Terrace Standard, March, 23, 1994

Crowdsourcing enables new possibilities for QoE evaluation by moving the evaluation task from the traditional laboratory environment into the Internet, allowing researchers to easily access a global pool of workers for the evaluation task. This makes it not only possible to include a more diverse population and real-life environments into the evaluation, but also reduces the turn-around time and increases the number of subjects participating in an evaluation campaign significantly, thereby circumventing bottle-necks in traditional laboratory setups. In order to utilise these advantages, the differences between laboratory-based and crowd-based QoE evaluation are discussed in this chapter.publishe

Challenges of future multimedia QoE monitoring for internet service providers

The ever-increasing network traffic and user expectations at reduced cost make the delivery of high Quality of Experience (QoE) for multimedia services more vital than ever in the eyes of Internet Service Providers (ISPs). Real-time quality monitoring, with a focus on the user, has become essential as the first step in cost-effective provisioning of high quality services. With the recent changes in the perception of user privacy, the rising level of application-layer encryption and the introduction and deployment of virtualized networks, QoE monitoring solutions need to be adapted to the fast changing Internet landscape. In this contribution, we provide an overview of state-of-the-art quality monitoring models and probing technologies, and highlight the major challenges ISPs have to face when they want to ensure high service quality for their customers

Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

This chapter presents the authors’ work for the Case Study entitled “Delivering Social Media with Scalability” within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the aforementioned action. The ease of user content generation within social media platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges: derivation of real-time meaningful insights from effectively gathered social information, a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general, etc. In this article we present the methodology we followed, the results of our work and the outline of a comprehensive survey, that depicts the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centers supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. The challenges of enabling better provisioning of social media data have been identified and they were based on the context of users accessing these resources. The existing literature has been systematized and the main research points and industrial efforts in the area were identified and analyzed. In our works, in the framework of the Action, we came up with potential solutions addressing the problems of the area and described how these fit in the general ecosystem

Towards a Socially-Aware Management of New Overlay Application Traffic Combined with Energy Efficiency in the Internet (SmartenIT)

The Internet has seen a strong move to support overlay applications, which demand a coherent and integrated control in underlying heterogeneous networks in a scalable, resilient, and energy-efficient manner. A tighter integration of network management and overlay service functionality can lead to crosslayer optimization of operations and management, which is a promising approach as it offers a large business potential in operational perspectives for all players involved. Therefore, the objective of this paper is to present SmartenIT (Socially-aware Management of New Overlay Application Traffic combined with Energy Efficiency in the Internet), which targets at an incentivecompatible cross-layer network management for providers of overlay-based application (e.g., cloud applications, content delivery, and social networks), network providers, and end-users. The goal is to ensure a QoE-awareness, by addressing accordingly load and traffic patterns or special application requirements, and exploiting at the same time social awareness (in terms of user relations and interests). Moreover, energy efficiency with respect to both end-user devices and underlying networking infrastructure is tackled to ensure an operationally efficient management. Incentive-compatible network management mechanisms for improving metrics on an inter-domain basis for ISPs serve as the major mechanism to deal with and investigate real-life scenarios