Accepted papers

Please note: The list of full papers and dataset papers is finalized. The list of short papers and demo papers is not finalized yet. The papers announced here are only the ones that are accepted and conditionally accepted with shepherding.
Full papers
Short papers
Dataset papers

Full papers

Receiver Driven Rate Adaptation
AngelCast: Cloud-based Peer-Assisted Live Streaming Using Optimized Multi-Tree Construction.
Spatio-Temporal Video Copy Detection
A Longitudinal View of HTTP Video Streaming Performance
The n-Dimensional Display Interface: A More Elastic Narrow Waist for the Display Pipeline
Multi-Video Summary and Skim Generation of Sensor-rich Videos in Geo-Space
Efficient Video Uploading from Mobile Devices in Support of HTTP Streaming
Copy Detection of 3D Videos
Shaping HTTP adaptive streams for a better user experience
Scheduler Support for Video-oriented Multimedia on Client-side Virtualization
QDASH: A QoE-aware DASH system
Mobile JND: Environment Adapted Perceptual Model and Mobile Video Quality Enhancement
Receiver Driven Rate Adaptation
Authors: D. Havey, R. Chertov, K. Almeroth
Abstract: Streaming video over the Internet to wireless mobile devices has seen a tremendous increase in popularity amongst users. Recent improvements in infrastructure have made the delivery of video over wireless a reality. However, user demand for high definition video streams promises to quickly devour the bandwidth provided by these improvements. In this paper, we explore the use of client driven application layer rate adaptation mechanisms that can achieve significant throughput increases as compared to a standard rate adaptive HTTP/TCP video stream operating over a wireless link. Our solution operates with standard HTTP/TCP video servers and requires no in-network modifications or kernel changes at the client. We demonstrate the performance improvements of our proposed system through both emulation and deployment on a wireless mesh network in South Africa.
AngelCast: Cloud-based Peer-Assisted Live Streaming Using Optimized Multi-Tree Construction.
Authors: R. Sweha, V. Ishakian, A. Bestavros
Abstract: Increasingly, commercial content providers (CPs) offer streaming and IPTV solutions that leverage an underlying peer-to-peer (P2P) stream distribution architecture. The use of P2P protocols promises significant scalability and cost savings by leveraging the local resources of clients -- specifically, uplink capacity. A major limitation of P2P live streaming is that playout rates are constrained by the uplink capacities of clients, which are typically much lower than downlink capacities, thus limiting the quality of the delivered stream. Thus, to leverage P2P architectures without sacrificing the quality of the delivered stream, CPs must commit additional resources to complement those available through clients. In this paper, we propose a cloud-based service - AngelCast- that enables CPs to elastically complement P2P streaming "as needed". By subscribing to AngelCast, a CP is able to deploy extra resources ("angels"), on-demand from the cloud, to maintain a desirable stream (bit-rate) quality. Angels need not download the whole stream (they are not "leachers"), nor are they in possession of it (they are not "seeders"). Rather, angels only relay (download once and upload as many times as needed) the minimal possible fraction of the stream that is necessary to achieve the desirable stream quality, while maximally utilizing available client resources. We provide a lower bound on the minimum amount of angel capacity needed to maintain a certain bit-rate to all clients, and develop a fluid model construction that achieves this lower bound. Realizing the limitations of the fluid model construction -- namely, succeptibility to potentially arbitrary start-up delays and significant degradation due to churn -- we present a practical multi-tree construction that captures the spirit of the optimal construction, while avoiding its limitations. In particular, our AngelCast protocol achieves near optimal performance (compared to the fluid-model construction) while ensuring a low startup delay by maintaining a logarithmic-length path between any client and the provider, and while gracefully dealing with churn by adopting a flexible membership management approach. We present the blueprints of a prototype implementation of AngelCast, along with experimental results confirming the feasibility and performance potential of our AngelCast service when deployed on PlanetLab and Emulab.
Spatio-Temporal Video Copy Detection
Authors: R. Harvey, M. Hefeeda
Abstract: Video copy detection algorithms are used to find copies of original video content even if the content has been altered. Given the prevalence of video recording and copying devices as well as the availability of many Internet sites for hosting videos, detecting video copies has become an important problem especially for companies interested in managing and controlling copyrights of their content.We propose a new content-based video copy detection algorithm. The proposed algorithm creates signatures that capture the spatial and temporal features of videos. These spatio-temporal signatures enable the algorithm to provide both high precision and recall. In addition, these signatures require small storage and are easy to compute and compare. Our extensive experimental analysis with a large video dataset shows that the proposed algorithm achieves high precision and recall values while remaining robust to many video transformations that commonly occur in practice. The algorithm is simple to implement and is more computationally efficient than previous algorithms in literature.
A Longitudinal View of HTTP Video Streaming Performance
Authors: L. Plissonneau, E. Biersack
Abstract: This paper investigates HTTP streaming traffic from an ISP perspective. As streaming traffic now represents nearly half of the residential Internet traffic, understanding its characteristics is important. We focus on two major video sharing sites, YouTube and DailyMotion. We use ten packet traces from a residential ISP network, five for ADSL and five for FTTH customers, captured between 2008 and 2011. Covering a time span of four years allows us to identify changes in the service infrastructure of some providers. From the packet traces, we infer for each streaming flow the video characteristics, such as duration and encoding rate, as well as TCP flow characteristics. %: minimum RTT, mean download rate, and mean loss rate. Using additional information from the BGP routing tables allows us to identify the originating Autonomous System (AS)\@. With this data, we can uncover: the server side distribution policy, the impact of the serving AS on the flow characteristics and the impact of the reception quality on user behavior. A unique aspect of our work is how to measure the reception quality of the video and its impact on the viewing behavior. We see that not even half of the videos are fully downloaded. For short videos of 3~minutes or less, users stop downloading at any point, while for videos longer than 3~minutes, users either stop downloading early on or fully download the video. When the reception quality deteriorates, fewer videos are fully downloaded, and the decision to interrupt download is taken earlier. We conclude that (i) the video sharing sites have a major control over the delivery of the video and its reception quality through DNS resolution and server side streaming policy, and (ii) that only half of the videos are fully downloaded and that this fraction dramatically drops when the video reception quality is bad.
The n-Dimensional Display Interface: A More Elastic Narrow Waist for the Display Pipeline
Authors: C. Estes, K. Mayer-Patel
Abstract: The framebuffer is a simple yet powerful software abstraction for representing display data. It ably serves as a “narrow waist” for the display pipeline, allowing graphics software and display technology to evolve in parallel. Converging trends such as mobile computing, very large displays, and 3DTV are challenging the inherent inefficiency of serializing and encoding the framebuffer tens or hundreds of times per second. In this paper, we present a flexible new software abstraction that can deliver tremendous channel efficiency when application level semantics are exploited. The goal is to develop a versatile interface from this elastic narrow waist that scales from very large displays to small, low-power displays connected over wireless links.
Multi-Video Summary and Skim Generation of Sensor-rich Videos in Geo-Space
Authors: Y. Zhang, G. Wang, B. Seo, R. Zimmermann
Abstract: User-generated videos have become increasingly popular in recent years. Due to advances in camera technology it is now very easy and convenient to record videos with mobile devices, such as smartphones. Here we consider an application where users collect and share a large set of videos that are related to a geographic area, say a city. Such a repository can be a great source of information for prospective tourists when they plan to visit a city and would like to get a preview of its main areas. The challenge that we address here is how to automatically create such a preview video summary from a large set of source videos. The main features of our technique are that it is fully automatic and leverages meta-data sensor information which is acquired in conjunction with videos. The meta-data is collected from GPS and compass sensors and is used to describe the viewable scenes of the videos. Our method then proceeds in three steps through the analysis of the sensor data. First, we generate a single video summary. Shot boundaries are detected based on different motion types of camera movements and key frames are extracted related to motion patterns. Second, we build video skims for popular places (i.e., hotspots) aiming to provide maximal coverage of hotspot areas with minimal redundancy (perspot multi-video summary). Finally, the individual hotspot skims are linked together to generate a pleasant video tour that visits all the popular places (multi-spot multi-video summary).
Efficient Video Uploading from Mobile Devices in Support of HTTP Streaming
Authors: B. Seo, W. Cui, R. Zimmermann
Abstract: Mobile video traffic is growing rapidly in networks due to the continuing user adoption of smartphones and tablet computers. While video viewing is now prevalent on such devices, they also easily enable the recording and uploading of videos for quick publishing on popular video sharing websites. Dynamic Adaptive Streaming over HTTP, or DASH, is a recent media streaming paradigm which has gained attention for its ability to enable media players to render videos with high quality under various network conditions. There is an effort under way to standardize DASH; however, the focus is currently limited to the efficient server-to-client distribution of videos. In our study we examine the common challenges that manifest themselves during the client-to-server uploading of mobile videos, for example unstable wireless connections and delayed video availability. We propose a new approach that provides compatibility with DASH and at the same time improves content availability by reducing the end-to-end delay from the recording time of mobile videos to the publishing of the first segment of the multi-bitrate encoded versions through a careful pipelining of the overall process. Our approach features (1) the use of segmentation of videos at the mobile device before uploading and (2) segment-wise transcoding and transformatting on the server side. Therefore, our solution does not require any dedicated encoder for live events while achieving semi-realtime live streaming and providing multi-bitrate content for user-generated videos from smartphones. We report on the performance of our prototype system which uses Android client devices.
Copy Detection of 3D Videos
Authors: N. Khodabakhshi, M. Hefeeda
Abstract: We present a novel system to detect copies of 3D videos. The system creates signatures from the depth signals of 3D videos. It also extracts visual features from video frames and creates compact spatial signatures for videos. The system then uses the depth and spatial signatures to compare a given query video versus a reference video database. The system returns a score indicating whether the query video matches any video in the reference video database, and in case of matching, which portion of the reference video matches the query video. The method is computationally ef- ﬁcient and can be implemented in distributed manner. The system can be used, for example, by video content owners, video hosting sites, and third-party companies to ﬁnd illegally copied 3D videos. To the best of our knowledge, this is the ﬁrst complete 3D video copy detection system in the literature. We implemented the proposed system and conducted a rigorous evaluation study using 3D videos with diverse properties. Our experimental results show that the proposed system can achieve high accuracy in terms of precision and recall even if the 3D videos are subjected to several transformations at the same time. For example, the proposed system yields 100% precesion and recall when copied videos are unmodiﬁed parts of original videos, and more than 90% precision and recall when copied videos are subjected to diﬀerent individual transformations.
Shaping HTTP adaptive streams for a better user experience
Authors: H. Remi, G. Stephane
Abstract: With increasing audio/video service consumption through unmanaged IP networks, HTTP adaptive streaming techniques have emerged to handle bandwidth limitations and variations. But while it is becoming common to serve multiple clients in one home network, these solutions do not adequately address fine tuned quality arbitration between the multiple streams. While clients compete for bandwidth, the video suffers unstable conditions and/or inappropriate bit-rate levels. We hereby propose mechanisms that allow an arbitration to be implemented by the home gateway, first determining desirable target bit-rates to be reached by each stream and then constraining the clients to stay within their limits. This enables the delivery of optimal quality of experience to the maximum number of users. This approach is validated through experimentation, and results are shown through a set of objective measurement criteria.
Scheduler Support for Video-oriented Multimedia on Client-side Virtualization
Authors: H. Kim, J. Jeong, J. Hwang, J. Lee, S. Maeng
Abstract: Virtualization has recently been adopted for client devices to provide strong isolation between services and efficient manageability. Even though multimedia service is not rare for the devices, the virtual machine hosting this service is not guaranteed to receive proper scheduling support from the underlying hypervisor. The quality of multimedia service is often compromised when several virtual machines compete for computing power. This paper presents a new scheduling scheme for the hypervisor to transparently identify if the workload handles multimedia and to provide proper scheduling supports. An implementation of our scheme has shown that the virtual machine hosting a video-oriented application receives propoer CPU scheduling even when other virtual machines host CPU intensive workloads.
QDASH: A QoE-aware DASH system
Authors: R. Mok, X. Luo, E. Chan, R. Chang
Abstract: Dynamic Adaptation Streaming over HTTP (DASH) enhances the Quality of Experience (QoE) for users by automatically switching quality levels according to network conditions. Various adaptation schemes have been proposed to select the most suitable quality level during video playback. Adaptation schemes are currently based on the measured TCP throughput received by the video player. Although video buffer can mitigate throughput fluctuations, it does not take into account the effect of the transition of quality levels on the QoE. In this paper, we propose a QoE-aware DASH system (or QDASH) to improve the user-perceived quality of video watching. We integrate available bandwidth measurement into the video data probes with a measurement proxy architecture. We have found that our available bandwidth measurement method facilitates the selection of video quality levels. Moreover, we assess the QoE of the quality transitions by carrying out subjective experiments. Our results show that users prefer a gradual quality change between the best and worst quality levels, instead of an abrupt switching. Hence, we propose a QoE-aware quality adaptation algorithm for DASH based on our findings. Finally, we integrate both network measurement and the QoE-aware quality adaptation into a comprehensive DASH system.
Mobile JND: Environment Adapted Perceptual Model and Mobile Video Quality Enhancement
Authors: J. Xue, C. Chen
Abstract: Design of a quality-of-experience (QoE) optimized mobile video system should consider not only the video content and display specifications but also the fact that mobile devices are exposed to many different environments and viewing scenarios. For same device and same content, the viewer will perceive different visual qualities when the viewing environment changes. Current perceptual quality estimation approaches including the extensively adopted just noticeable distortion (JND) based models neglect significant influence of surroundings on perception. However, the environmental effects on perception have long been supported by psychophysical experiments. This paper proposes a novel viewing scenario adapted model that exploits the influence of various viewing conditions including display size, viewing distance, ambient luminance and body movement and apply the proposed model to the H.264 video encoding. With the help of multiple sensors widely equipped on handholds today, the mobile device is able to dynamically estimate the surrounding conditions. The estimated environment parameters are feedback to video encoder to generate encoded video source that best matches to the current scenario so as to improve the bandwidth efficiency and enhance visual quality for that particular environment. Our subjective experiments demonstrate a significant 30% saving on bit-rates without perceivable quality loss, or obvious improvements in visual qualities under same bandwidth constraint.

Short papers

Graph-Based Combinations of Fragment Descriptors for Improved 3D Object Retrieval
Towards the Understanding of Human Perceptual Quality in Tele-immersive Shared Activity
Adaptive Scalable Video Streaming in Wireless Networks
Adaptive 3D Texture Streaming in M3G-based Mobile Games
A New Signal Processing Method for Video
Synchronized Delivery of Multimedia Content over Uncoordinated Broadcast Broadband Networks
P2P Streaming: a Study on the Use of Advertisements as Incentives
Collaborative Caching for Efficient Dissemination of Personalized Video Streams in Resource Constrained Environments
Graph-Based Combinations of Fragment Descriptors for Improved 3D Object Retrieval
Authors: T. Schreck, M. Scherer, M. Walter, B. Bustos, S. Yoon, A. Kuijper
Abstract: 3D Object Retrieval is an important field of research with many application possibilities. One of the main goals in this research is the development of discriminative methods for similarity search. The descriptor-based approach to date has seen a lot of research attention, with many different extraction algorithms proposed. In previous work, we have introduced a simple but effective scheme for 3D model retrieval based on a spatially fixed combination of 3D object fragment descriptors. In this work, we propose a novel flexible combination scheme based on finding the best matching fragment descriptors to use in the combination. By an exhaustive experimental evaluation on established benchmark data we show the capability of the new combination scheme to provide improved retrieval effectiveness. The method is proposed as a versatile and inexpensive method to enhance the effectiveness of a given global 3D descriptor approach.
Towards the Understanding of Human Perceptual Quality in Tele-immersive Shared Activity
Authors: Z. Huang, A. Arefin, P. Agarwal, K. Nahrstedt, W. Wu
Abstract: Both comparative category rating (CCR) and degradation category rating (DCR) methods have been heavily employed in the subjective evaluations of media systems. The resulting metrics, comparative mean-opinion-score (CMOS) and degradation mean-opinion-score (DMOS), can be used to describe the system subjective quality. However, the subjective metrics may work unsuccessfully when the variance of participant votes is large. The diversity in human interests can appear due to the tradeoffs of multiple quality dimensions, which concurrently dominate the overall quality of the media system. In this paper, we conduct a user study with 19 participants to evaluate the subjective quality of two tele-immersive shared activities (TISA), where media samples of different qualities are evaluated in case of each activity. Our study aims at (1) showing the effectiveness and limitation of CMOS and DMOS using real subjective data, and (2) demonstrating the heterogeneous impacts of TISAs on human perceptions.
Adaptive Scalable Video Streaming in Wireless Networks
Authors: S. Xiang, L. Cai, J. Pan
Abstract: In this paper, we investigate the optimal streaming strategy for dynamic adaptive streaming over HTTP (DASH). Specifically, we focus on the rate adaptation algorithm for streaming scalable video (H.264/SVC) in wireless networks. We model the rate adaptation problem as a Markov Decision Process (MDP), aiming to find an optimal streaming strategy in terms of user-perceived quality of experience (QoE) such as playback interruption, average playback quality and playback smoothness. We then obtain the optimal MDP solution using dynamic programming. We further define a reward parameter in our proposed streaming strategy, which can be adjusted to make a good trade-off between the average playback quality and playback smoothness. We also use a simple testbed to verify our solution. Experiment results show the feasibility of the proposed solution and its advantage over the existing work.
Adaptive 3D Texture Streaming in M3G-based Mobile Games
Authors: M. Hosseini, D. Ahmed, S. Shirmohammadi
Abstract: With the growing demand of mobile applications and games, one of the challenges is how to efficiently transmit the bulky 3D information to bandwidth- and computationally-limited mobile devices. In this paper, we propose two methods for improving the transmission delay of M3G-based 3D mobile game content over unreliable and congested networks. We introduce Object Mesh Similarity as a server side approach, in which we try to detect an alternative object with minimum complexities that is similar to the original object, and then transmit this reconstructed object, as well as Texture Stretching as a client-side approach, which leads to the efficient receipt of object textures. Our results show 35% to 70% improvement in the transmission delay of 3D textures.
A New Signal Processing Method for Video
Authors: S. Gohshi
Abstract: A new signal processing method to improve video image quality is proposed in this paper. Improving video image resolution has been researched for many years. The method of edge enhancing is usually known as Sharpness Circuit (SC), Enhancer or Un-sharp Mask,. It is widely used since it works in real time and it is low cost. However, edge enhancing does not actually improve the degree of resolution but increases perceived resolution. It is almost impossible to create components exceeding the Nyquist frequency using conventional linear signal processing methods. Super Resolution (SR) is a highly interesting research field and many ideas and methods have been proposed, some of which have the potential to actually enhance resolution. However, these ideas have not been widely discussed in the frequency domain. A new signal processing method that creates components exceeding the Nyquist frequency is proposed. The simulation results are discussed with regard to time domain as well as to the frequency domain.
Synchronized Delivery of Multimedia Content over Uncoordinated Broadcast Broadband Networks
Authors: C. Concolato, S. Thomas, R. Bouqueau, J. Feuvre
Abstract: Existing broadcast networks can deliver identical content to a large number of users. Broadband networks can deliver personalized content to specific users. Hybrid delivery tries to use the best of both types of networks to provide customized services to many users. This paper studies the theoretical aspects and challenges behind the delivery of multimedia content over hybrid broadcast broadband networks, including bootstrapping, synchronization and resynchronization. It presents a solution based on the use of a global clock which does not require communication across networks and is compatible with existing technologies. This solution is implemented in a multimedia player and evaluated against two real-world scenarios, mixing DVB or FM networks with a broadband IP network. The results confirm the theoretical approach and show that some fine tuning in the networks is needed for a tighter synchronization.
P2P Streaming: a Study on the Use of Advertisements as Incentives
Authors: B. Wang, A. Chow, L. Golubchik
Abstract: P2P streaming systems, such as PPLive, PPStream, and TVUPlayer, have become popular services with the widespread deployment of broadband networks. However, P2P streaming systems still face free-riding problems, similar to those that have been observed in P2P file sharing systems. Thus, one important problem in providing streaming services is that of providing appropriate incentives for peers to contribute their upload capacity. To this end, we propose the use of advertisements as an incentive for peers to contribute upload capacity. In the proposed framework, peers enjoy the same quality of streamed media, with the difference in quality of service being achieved through different amounts of advertisements viewed, based on the resource contributions to the system. An extensive simulation-based study is performed to evaluate the proposed approach. The results demonstrate that our approach provides appropriate incentives for peers to contribute their resources.
Collaborative Caching for Efficient Dissemination of Personalized Video Streams in Resource Constrained Environments
Authors: S. Bhandarkar, L. Ramaswamy, H. Devulapally
Abstract: The ever increasing deployment of broadband networks and simultaneous proliferation of low-cost video capturing and multimedia-enabled mobile devices such as smart cellular phones, personal digital assistants (PDA's), pocket PC's and netbook PC's have triggered a wave of novel mobile multimedia applications resulting in the development of large scale systems for delivery of video to heterogeneous mobile clients. Networked environments consisting of these mobile devices tend to be highly heterogeneous in terms of client-side and system-wide resource constraints, clients' queries for information, geospatial distribution and dynamic trajectories of the mobile clients, and client-side and server-side privacy requirements. Hence, the video streams need to be personalized to provide the resource-constrained mobile devices with video content that is most relevant to the client's request while simultaneously satisfying the client-side and system-wide resource constraints, client-side and server-side security and privacy requirements and the constraints imposed by the geospatial distribution and dynamic trajectories of the mobile clients relative to the server(s). However, video personalization imposes a significant resource overhead on the origin servers and on the network, making efficient dissemination of personalized video in a resource-constrained mobile environment a significant challenge. In this paper we present the design and implementation of a system for efficient dissemination of personalized video in a resource-constrained mobile environment. The proposed system comprises of one or more video personalization servers and several geographically distributed caches. The video personalization servers employ an automatic video segmentation and video indexing scheme based on semantic analysis of video content and a video personalization scheme based on determining an optimal solution to the Multiple-Choice Multi-Dimensional Knapsack Problem (MMKP). With the objective of optimizing cache performance, a novel cache replacement policy and multi-stage client request aggregation strategy, both of which are specifically tailored for personalized video content, are proposed. A collaborative caching mechanism is designed for further enhancing the scalability and efficiency of disseminating personalized video content. The benefits and costs associated with collaborative caching for disseminating personalized video content to resource-constrained and geographically distributed clients are analyzed and experimentally verified. The impact of different levels of collaboration amongst the caches and the advantages of using multiple video personalization servers with varying degrees of mirrored content on the efficiency of personalized video delivery are also studied.

Dataset papers

6DMG: A New 6D Motion Gesture Database
Dynamic Adaptive Streaming over HTTP Dataset
Network Traffic from Anarchy Online: Analysis, Statistics and Applications
6DMG: A New 6D Motion Gesture Database
Authors: M. Chen, G. AlRegib, B. Juang
Abstract: Motion-based control is gaining popularity, and motion gestures form a complementary modality in human-computer interactions. To achieve more robust userindependent motion gesture recognition in a manner analogous to automatic speech recognition, we need a deeper understanding of the motions in gesture, which arouses the need for a 6D motion gesture database. In this work, we present a database that contains comprehensive motion data, including the position, orientation, acceleration, and angular speed, for a set of common motion gestures performed by different users. We hope this motion gesture database can be a useful platform for researchers and developers to build their recognition algorithms as well as a common test bench for performance comparisons.
Dynamic Adaptive Streaming over HTTP Dataset
Authors: S. Lederer, C. Müller, C. Timmerer
Abstract: Adaptive HTTP streaming got lot of attention in recent years and with dynamic adaptive streaming over HTTP (DASH) a standard is available. Many papers cover this topic and present their research results, but unfortunately all of them use their own private dataset which – in most cases – is not publicly available. Hence, it is difficult to compare, e.g., adaptation algorithms in an objective way due to the lack of a common dataset which shall be used as basis for such experiments. In this paper, we present our DASH dataset featuring our DASHEncoder, an open source DASH content generation tool. We also provide basic evaluations of the different segment lengths, the influence of HTTP server settings, and, in this context, we show some of the advantages as well as problems of shorter segment lengths.
Network Traffic from Anarchy Online: Analysis, Statistics and Applications
Authors: A. Petlund, P. Halvorsen, P. Hansen, T. Lindgren, R. Casais, C. Griwodz
Abstract: We present a dataset – a real-world, server-side packet trace – from Anarchy Online. Anarchy Online is a science fiction-themed massively multiplayer online roleplaying game (MMORPG), published and developed by Funcom. We present statistics from the network traffic and show that it is a representative dataset for similar games. From the dataset, one can extract several key characteristics from such scenarios like payload sizes, packet rates, data delivery latencies, retransmission statistics, loss rates and stream correlation. The dataset can be used several ways: by replaying the game traffic, components like congestion control mechanisms, middlewares, packet schedulers, router queue behaviour, etc. can be analysed. Based on the observed statistics from the trace, such interactive game traffic shows completely different behaviour compared to the greedy, high-rate streams most network mechanisms are designed for, e.g., file download, video streaming and web-surfing. We hope that the dataset can be used to push research forward in the field of system support for games.