Latency and player actions in online games

The growth and penetration of broadband access networks to the home has fueled the growth of online games played over the Internet. As we write this article, it is 5am on a typical weekday morning and Gamespy Arcade 1 reports more than 250,000 players online playing about 75,000 games! This proliferation of online games has been matched by an equivalent growth in both th

Power-Constrained Fuzzy Logic Control of Video Streaming over a Wireless Interconnect

Wireless communication of video, with Bluetooth as an example, represents a compromise between channel conditions, display and decode deadlines, and energy constraints. This paper proposes fuzzy logic control (FLC) of automatic repeat request (ARQ) as a way of reconciling these factors, with a 40% saving in power in the worst channel conditions from economizing on transmissions when channel errors occur. Whatever the channel conditions are, FLC is shown to outperform the default Bluetooth scheme and an alternative Bluetooth-adaptive ARQ scheme in terms of reduced packet loss and delay, as well as improved video quality

Ordonnanceurs hiérarchiques adaptables

National audienceLes systèmes d'exploitation à temps partagé offrent à l'utilisateur un confort d'utilisation en permettant de simuler l'exécution simultanée de plusieurs programmes. Pour cela le système traite équitablement et à tour de rôle chacune des tâches pendant un quantum de temps défini. L'inconvénient est que l'utilisateur peut exécuter différentes catégories de programmes ne reposant pas sur les mêmes critères. Les applications multimédias, comme la lecture d'un fichier vidéo, peuvent souffrir de cette équité dès lors qu'un certain nombre de programmes s'exécutent. Lorsqu'elles ne possèdent pas les ressources suffisantes elles deviennent inutilisables : les images ne sont plus synchronisées avec la bande son et l'affichage devient saccadé. Cependant, toutes les applications ne nécessitent pas de contraintes temporelles et, par exemple, les traitements de données ne sont pas altérés si les résultats sont produits avec du retard. Nous présentons nos travaux sur la plate forme MVV-Bossa qui fournit à l'utilisateur un moyen de casser l'équité entre les différentes tâches et donc lui permet de mettre l'accent sur l'exécution d'un programme particulier pour obtenir la qualité de service qu'il désire

SCOPE: Synergistic Content Distribution and Peer-to-Peer Networks

Distributing content on the Internet is an important economic, educational, social, and cultural endeavor. To this end, several existing efforts use traditional server-based content distribution networks (CDNs) to replicate and distribute Web and multimedia content of big content producers, such as news Web sites, or big businesses, such as online shopping websites, etc., to millions of Internet users. This approach places a large number of content servers at strategic locations on the Internet, incurring a very large deployment and operating cost. Therefore, it is available only to some wealthy companies/organizations. Individual users and small content publishers may rely on a more economical content dissemination approach based on recent peer-to-peer technology to distribute their own content. Nevertheless, it is the ephemeral and the limited resources nature of peer-to-peer networks that hinder a wide spread adoption of peer-to-peer technology as a reliable content distribution solution. It is, therefore, important that a new generation of cost-effective and reliable content distribution framework be proposed and investigated. Building on the successes and failures of previous content distribution approaches, the proposed research goal is to find and evaluate a Synergistic Content Distribution and Peer-to-Peer Networks (SCOPE). SCOPE leverages the reliability and the resourcefulness of traditional server-based CDNs while tapping on the economical and dynamic resources of peers

The Process of Creation: A Novel Methodology for Analyzing Multimodal Data

In the 21st century, meaning making is a multimodal act; we communicate what we know and how we know it using much more than printed text on a blank page. As a result, qualitative researchers need new methodologies, methods, and tools for working with the complex artifacts that our research subjects produce. In this article we describe the co-development of an analytic methodology and a tool for working with youth produced films as multimodal artifacts of youth engagement with identity. Specifically, we describe how to employ this multimodal framework in data analysis, with an emphasis on how different modes interact with one another, and how new meanings are made possible through multimodal interactions

Improving video streaming experience through network measurements and analysis

Multimedia traffic dominates today’s Internet. In particular, the most prevalent traffic carried over wired and wireless networks is video. Most popular streaming providers (e.g. Netflix, Youtube) utilise HTTP adaptive streaming (HAS) for video content delivery to end-users. The power of HAS lies in the ability to change video quality in real time depending on the current state of the network (i.e. available network resources). The main goal of HAS algorithms is to maximise video quality while minimising re-buffering events and switching between different qualities. However, these requirements are opposite in nature, so striking a perfect blend is challenging, as there is no single widely accepted metric that captures user experience based on the aforementioned requirements. In recent years, researchers have put a lot of effort into designing subjectively validated metrics that can be used to map quality, re-buffering and switching behaviour of HAS players to the overall user experience (i.e. video QoE). This thesis demonstrates how data analysis can contribute in improving video QoE. One of the main characteristics of mobile networks is frequent throughput fluctuations. There are various underlying factors that contribute to this behaviour, including rapid changes in the radio channel conditions, system load and interaction between feedback loops at the different time scales. These fluctuations highlight the challenge to achieve a high video user experience. In this thesis, we tackle this issue by exploring the possibility of throughput prediction in cellular networks. The need for better throughput prediction comes from data-based evidence that standard throughput estimation techniques (e.g. exponential moving average) exhibit low prediction accuracy. Cellular networks deploy opportunistic exponential scheduling algorithms (i.e. proportional-fair) for resource allocation among mobile users/devices. These algorithms take into account a user’s physical layer information together with throughput demand. While the algorithm itself is proprietary to the manufacturer, physical layer and throughput information are exchanged between devices and base stations. Availability of this information allows for a data-driven approach for throughput prediction. This thesis utilises a machine-learning approach to predict available throughput based on measurements in the near past. As a result, a prediction accuracy with an error less than 15% in 90% of samples is achieved. Adding information from other devices served by the same base station (network-based information) further improves accuracy while lessening the need for a large history (i.e. how far to look into the past). Finally, the throughput prediction technique is incorporated to state-of-the-art HAS algorithms. The approach is validated in a commercial cellular network and on a stock mobile device. As a result, better throughput prediction helps in improving user experience up to 33%, while minimising re-buffering events by up to 85%. In contrast to wireless networks, channel characteristics of the wired medium are more stable, resulting in less prominent throughput variations. However, all traffic traverses through network queues (i.e. a router or switch), unlike in cellular networks where each user gets a dedicated queue at the base station. Furthermore, network operators usually deploy a simple first-in-first-out queuing discipline at queues. As a result, traffic can experience excessive delays due to the large queue sizes, usually deployed in order to minimise packet loss and maximise throughput. This effect, also known as bufferbloat, negatively impacts delay-sensitive applications, such as web browsing and voice. While there exist guidelines for modelling queue size, there is no work analysing its impact on video streaming traffic generated by multiple users. To answer this question, the performance of multiple videos clients sharing a bottleneck link is analysed. Moreover, the analysis is extended to a realistic case including heterogeneous round-trip-time (RTT) and traffic (i.e. web browsing). Based on experimental results, a simple two queue discipline is proposed for scheduling heterogeneous traffic by taking into account application characteristics. As a result, compared to the state-of-the-art Active Queue Management (AQM) discipline, Controlled Delay Management (CoDel), the proposed discipline decreases median Page Loading Time (PLT) of web traffic by up to 80% compared to CoDel, with no significant negative impact on video QoE

An Information-Theoretic Framework for Consistency Maintenance in Distributed Interactive Applications

Distributed Interactive Applications (DIAs) enable geographically dispersed users to interact with each other in a virtual environment. A key factor to the success of a DIA is the maintenance of a consistent view of the shared virtual world for all the participants. However, maintaining consistent states in DIAs is difficult under real networks. State changes communicated by messages over such networks suffer latency leading to inconsistency across the application. Predictive Contract Mechanisms (PCMs) combat this problem through reducing the number of messages transmitted in return for perceptually tolerable inconsistency. This thesis examines the operation of PCMs using concepts and methods derived from information theory. This information theory perspective results in a novel information model of PCMs that quantifies and analyzes the efficiency of such methods in communicating the reduced state information, and a new adaptive multiple-model-based framework for improving consistency in DIAs. The first part of this thesis introduces information measurements of user behavior in DIAs and formalizes the information model for PCM operation. In presenting the information model, the statistical dependence in the entity state, which makes using extrapolation models to predict future user behavior possible, is evaluated. The efficiency of a PCM to exploit such predictability to reduce the amount of network resources required to maintain consistency is also investigated. It is demonstrated that from the information theory perspective, PCMs can be interpreted as a form of information reduction and compression. The second part of this thesis proposes an Information-Based Dynamic Extrapolation Model for dynamically selecting between extrapolation algorithms based on information evaluation and inferred network conditions. This model adapts PCM configurations to both user behavior and network conditions, and makes the most information-efficient use of the available network resources. In doing so, it improves PCM performance and consistency in DIAs

AXMEDIS 2007 Conference Proceedings

The AXMEDIS International Conference series has been established since 2005 and is focused on the research, developments and applications in the cross-media domain, exploring innovative technologies to meet the challenges of the sector. AXMEDIS2007 deals with all subjects and topics related to cross-media and digital-media content production, processing, management, standards, representation, sharing, interoperability, protection and rights management. It addresses the latest developments and future trends of the technologies and their applications, their impact and exploitation within academic, business and industrial communities