Osama Abboud

Impact of frame rate and resolution on objective QoE metrics

Video streaming applications are a major driver for the evolution of the future Internet. In this paper we introduce a framework for QoE management for video streaming systems based on the H.264/SVC codec, the scalable extension of H.264/AVC. A relevant feature is to control the user perceived quality of experience (QoE) by exploiting parameters offered by SVC. A proper design of a control mechanism requires the quantification of the main influence parameters on the QoE. For this purpose, we conducted a measurement study and quantified the influence of i) video resolution, ii) scaling method, iii) video frame rate and iv) video content types on the QoE by means of the SSIM and VQM full-reference metrics. Further, we discuss the trade-off between these different control knobs and their influence on the QoE.

On the impact of quality adaptation in SVC-based P2P video-on-demand systems

P2P Video-on-Demand (VoD) based on Scalable Video Coding (SVC) (the scalable extension of the H.264/AVC standard) is gaining momentum in the research community, as it provides elegant adaptation to heterogeneous resources and network dynamics. The major question is, how do the adaptation algorithms and designs affect the overall perceived performance of the system? Better yet, how can the performance of an SVC-based VoD system be defined? This paper explores the impact and trade-offs of SVC-based quality adaptation with focus on the SVC layer selection algorithms, which are performed at different streaming stages. We carry out extensive experiments to evaluate the performance in terms of session quality (start-up delay, video stalls) and delivered SVC video quality (layer switches, received layers), and find out that these two metrics exhibit a trade-off. Our analysis and conclusions give multimedia providers insights on how to design and fine-tune their VoD system in order to achieve best performance.

Enabling resilient P2P video streaming: survey and analysis

Peer-to-Peer (P2P) techniques for multimedia streaming have been shown to be a good enhancement to the traditional client/server methods when trying to reduce costs and increase robustness. Due to the fact that P2P systems are highly dynamic, the main challenge that has to be addressed remains supporting the general resilience of the system. Various challenges arise when building a resilient P2P streaming system, such as network failures and system dynamics. In this paper, we first classify the different challenges that face P2P streaming and then present and analyze the possible countermeasures. We classify resilience mechanisms as either core mechanisms, which are part of the system, or as cross-layer mechanisms that use information from different communication layers, which might inflict additional costs. We analyze and present resilience mechanisms from an engineering point of view, such that a system engineer can use our analysis as a guide to build a resilient P2P streaming system with different mechanisms and for various application scenarios.

Quality Adaptive Peer-to-Peer Streaming Using Scalable Video Coding

P2P (Peer-to-Peer) video streaming has attracted much attention recently. However, streaming over P2P is still best effort and suffers from lack of adaptation. Therefore, video streaming over P2P either works or not. In this paper, we propose a P2P streaming system with an inherent support for adaptation. By leveraging scalable video coding, our system is able to adapt to different requirements and constraints that heterogeneous peers have in todays Internet. We make a subtle distinction between initial and progressive quality adaptation, which allows for precise adaptation to various parameters of the system and the P2P network. Our decision-taking algorithms for quality adaptation help not only in perfectly matching QoS to resources but also in bringing the P2P network to self organization.

Underlay awareness in P2P systems: Techniques and challenges

Peer-to-peer (P2P) applications have recently attracted a large number of Internet users. Traditional P2P systems however, suffer from inefficiency due to lack of information from the underlay, i.e. the physical network. Although there is a plethora of research on underlay awareness, this aspect of P2P systems is still not clearly structured. In this paper, we provide a taxonomic survey that outlines the different steps for achieving underlay awareness. The main contribution of this paper is presenting a clear picture of what underlay awareness is and how it can be used to build next generation P2P systems. Impacts of underlay awareness and open research issues are also discussed.

Quality adaptation in p2p video streaming based on objective qoe metrics

The transmission of video data is a major part of traffic on todays Internet. Since the Internet is a highly dynamic environment, quality adaptation is essential in matching user device resources with the streamed video quality. This can be achieved by applying mechanisms that follow the Scalable Video Coding (SVC) standard, which enables scalability of the video quality in multiple dimensions. In SVC-based streaming, adaptation decisions have long been driven by Quality of Service (QoS) metrics, such as throughput. However, these metrics do not well match the way human users perceive video quality. Therefore, in this paper, the classical SVC-based video streaming approach is expanded to consider Quality of Experience (QoE) for adaptation decisions. The video quality is assessed using existing objective techniques with a high correlation to the human perception. The approach is evaluated in context of a P2P-based Video-on-Demand (VoD) system and shows that by making peers favor always layers with a high estimated QoE but not necessarily high bandwidth requirements, the performance of the entire system can be enhanced in terms of playback delay and SVC video quality by up to 20%. At the same time, content providers are able to reduce up to 60 of their server costs, compared to the classical QoS-based approach.

StreamSocial: A P2P streaming system with social incentives

P2P Streaming has attracted much attention recently with promises for more revenues and better load distribution. In parallel, social networking has changed how people interact using the web. One interesting use-case for next generation IPTV is Social TV. In such a system, users are able to watch some media stream and interact with each other at the same time. While deploying P2P Social TV, one inherent problem in P2P streaming systems remains, how to incite users to contribute. In this demonstration we show how social networks can be used to build new incentive mechanisms. Rather than making social relations a mere addition, we build our streaming system on top of a users social network. This design greatly simplifies the system and requires no further entities for management. In this demonstration we present the first version of StreamSocial that, based on a plug-in based design, allows users to stream videos while performing social interactions.

A QoE-Aware P2P Streaming System Using Scalable Video Coding

P2P streaming has attracted much attention recently with promises for higher revenues and better load distribution. Still, the majority of P2P video streaming systems today employ the one-size-fits-all concept where the same video bit-rate is offered to all users. Here the promising H.264/Scalable Video Coding (SVC) standard is seen as a necessity in not only supporting heterogeneous resources, but also in reducing the impact of P2P dynamics on the perceived Quality-of-Experience (QoE). In this demonstration we present our streaming application that uses SVC to adapt to different user requirements and resources. The application employs a novel QoE- aware layer selection algorithm that maximizes flexibility through SVC while taking impact on QoE into consideration.

On energy-awareness for peer-assisted streaming with set-top boxes

Energy consumption is responsible for a large fraction of costs in todays content distribution networks. In upcoming decentralized architectures based on set-top boxes (STB), acting as tiny servers, idle times can dominate distribution costs, since no cooling costs occurs and the Internet access is often paid in a flat-rate manner. The often assumed always-on property of STBs provides high availability but might also waste up to 93% of the baseline energy. In this paper we consider suitable standby policies that reduce energy consumption but still allow offloading content servers significantly. We devise optimal and heuristic standby policies and evaluate them in a realistic scenario to show that a near-optimal behavior can be reached by utilizing the specific features of STBs.

Adaptive server allocation for peer-assisted Video-on-Demand

Dedicated servers are an undesirable but inevitable resource in peer-assisted streaming systems. Their provision is necessary to guarantee a satisfying quality of experience to consumers, yet they cause significant, and largely avoidable cost for the provider, which can be minimized. We propose two adaptive server allocation schemes that estimate the capacity situation and service demand of the system to adaptively optimize allocated resources. Extensive simulations support the efficiency of our approach, which, without considering any prior knowledge, allows achieving a competitive performance compared to systems that are well dimensioned using global knowledge.