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In recent years, Dynamic Adaptive Streaming over HTTP (DASH) has emerged as a popular adaptive video streaming technique to improve the bandwidth utilization. Moreover, DASH with segment-based flexibility also brings a potential benefit for the end user's Quality of Experience (QoE)1. Despite the tremendous popularity of technology like DASH, video delivery over the mobile networks is still facing some serious challenges.

While Internet video control and data planes have received much research attention, little is known about the video management plane. In this paper, using data from more than a hundred video publishers spanning two years, we characterize the video management plane and its evolution. The management plane shows significant diversity with respect to video packaging, playback device support, and CDN use, and current trends suggest increasing diversity in some of these dimensions. This diversity adds complexity to management, and we show that the complexity of many management tasks is sub-linearly correlated with the number of hours a publisher's content is viewed. Moreover, today each publisher runs an independent management plane, and this practice can lead to sub-optimal outcomes for syndicated content, such as redundancies in CDN storage and loss of control for content owners over delivery quality.

Various trends are reshaping Internet video delivery: exponential growth in video traffic, rising expectations of high video quality of experience (QoE), and the proliferation of varied content delivery network (CDN) deployments (e.g., cloud computing-based, content provider-owned datacenters, and ISP-owned CDNs). More fundamentally though, content providers are shifting delivery from a single CDN to multiple CDNs, through the use of a content broker. Brokers have been shown to invalidate many traditional delivery assumptions (e.g., shifting traffic invalidates short- and long-term traffic prediction) by not communicating their decisions with CDNs. In this work, we analyze these problems using data from a CDN and a broker. We examine the design space of potential solutions, finding that a marketplace design (inspired by advertising exchanges) potentially provides interesting tradeoffs. A marketplace allows all CDNs to profit on video delivery through fine-grained pricing and optimization, where CDNs learn risk-adverse bidding strategies to aid in traffic prediction. We implement a marketplace-based system (which we dub Video Delivery eXchange or VDX) in CDN and broker data-driven simulation, finding significant improvements in cost and data-path distance.

Recent years have witnessed a new video delivery paradigm: smartrouter-based peer video content delivery network, which is enabled by smartrouters deployed at users' homes. ChinaCache (one of the largest CDN providers in China) and Youku (a video provider using smartrouters to assist video delivery) announced their cooperation in 2015, to create a new paradigm of content delivery based on householders' network resources [2]. This new paradigm is different from the conventional peer-to-peer (P2P) approach, because millions of dedicated smartrouters are operated by the centralized video service providers in a coordinative manner. Thus it is intriguing to study the content placement strategies used in a smartrouter-based content delivery system, as well as its potential impact on the content delivery ecosystem. In this paper, we carry out measurement studies of Youku's peer video CDN, who has deployed over 300K smartrouter devices for its video delivery. In our measurement studies, 104K videos were investigated and 4TB traffic has been analyzed, over controlled smartrouter nodes and players. Our measurement insights are as follows. First, a global content replication strategy is essential for the peer CDN systems. Second, such peer CDN deployment itself can form an effective sub-system for end-to-end QoS monitoring, which can be used for fine-grained request redirection (e.g., user-level) and content replication. We also show our analysis on the performance limitations and propose potential improvements to the peer CDN systems.

HTTP adaptive streaming is increasingly popular in video delivery. This is mainly because HTTP allows easy deployment while it simplifies content delivery, and chunk-based delivery enables dynamic adaptation of video quality to varying network bandwidth. However, we find that the very nature of chunk delivery on HTTP causes some fundamental problems in efficient bandwidth utilization.In this work, we investigate why it is so hard to adapt to varying bandwidth with HTTP adaptive streaming. First, we find that the choice of chunk duration greatly affects the bandwidth adaptation logic. Second, we observe that the disparity between the advertised quality of a chunk and real encoding rate confuses the client-side adaptation logic. Third, the dependence on TCP/HTTP leads to suboptimal bandwidth utilization while it makes it challenging to adapt to rapidly-changing bandwidth. We show the evidence of the problems in our controlled experiments with popular HTTP adaptive streaming schemes, and lay out the future requirements for robust bandwidth adaptation in video streaming.

In recent years, video-on-demand services such as YouTube or Hulu have become popular. These VoD services often adopt P2P (Peer-to-Peer) streaming techniques to manage many users' requests. Some services provide different quality services for the users. For example, the users who pay money for the service provider can watch high-quality videos, and others can only watch low-quality videos. In such a multiple bit rate video delivery, since high-quality videos have high bit rate, their interruption time is very long compared with that for low-quality videos when many peers watch high-quality videos. In this paper, we propose a method to reduce interruption time for users watching high-quality videos in multiple bit rate video delivery. Our evaluation results show that our proposed method can reduce their interruption times.

It is our pleasure to welcome you to the Thirteenth ACM SIGCOMM Workshop on Hot Topics in Networks---HotNets 2014. The workshop strives to provide a venue for publication and discussion of early-stage, provocative research. We received 118 submissions and accepted 26 papers covering the global Internet, network management, wireless networks, video delivery, application-awareness, security, anonymity, network programmability, and more. The authors spanned 40 institutions and 11 countries.

In this work we model video delivery under expected periods of disconnection, such as the ones experienced in public transportation systems. Our main goal is to quantify the gains of users' collaboration in terms of Quality of Experience (QoE) in the context of intermittently available and bandwidth-limited WiFi connectivity. Under the assumption that Wi-Fi connectivity is available within underground stations, but absent between them, at first, we define a mathematical model which describes the content distribution under these conditions and we present the users' QoE function in terms of undisrupted video playback. Next, we expand this model to include the case of collaboration between users for content sharing in a peer-to-peer (P2P) way. Lastly, we evaluate our model based on real data from the London Underground network, where we investigate the feasibility of content distribution, only to find that collaboration between users increases significantly their QoE.

We propose a content and buffer aware Long Term Evolution (LTE) downlink scheduler for allocating radio resources to multiple users requesting Scalable Video Coding (SVC) encoded videos from a server. The scheduler adaptively controls the video quality by assigning physical resource blocks (PRBs) to the users based on the requested video type, device capability, channel quality, and buffer state in the user equipment (UE). The scheduler maximizes the average video quality across all users for a limited number of PRBs, and can be installed in existing LTE systems without additional equipment and very limited signaling overhead.

Online video is the killer application of the Internet. Videos are expected to constitute more than 85% of the traffic on the consumer Internet within the next few years. However, a vexing problem for video providers is how to monetize their online videos. A popular monetization model pursued by many major video providers is inserting ads that play in-stream with the video that is being watched. Our work represents the first rigorous scientific study of the key factors that determine the effectiveness of video ads as measured by their completion and abandonment rates. We collect and analyze a large set of anonymized traces from Akamai's video delivery network consisting of about 65 million unique viewers watching 362 million videos and 257 million ads from 33 video providers around the world. Using novel quasi-experimental techniques, we show that an ad is 18.1% more likely to complete when placed as a mid-roll than as a pre-roll, and 14.3% more likely to complete when placed as pre-roll than as a post-roll. Next, we show that completion rate of an ad decreases with increasing ad length. A 15-second ad is 2.9% more likely to complete than a 20-second ad, which in turn is 3.9% more likely to complete than a 30-second ad. Further, we show the ad completion rate is influenced by the video in which the ad is placed. An ad placed in long-form videos such as movies and TV episodes is 4.2% more likely to complete than the same ad placed in short-form video such as news clips. Finally, we show that about one-third of the viewers who abandon leave in the first quarter of the ad, while about two-thirds leave at the half-way point in the ad.Our work represents a first step towards scientifically understanding video ads and viewer behavior. Such understanding is crucial for the long-term viability of online videos and the future evolution of the Internet.

We demonstrate EigenNews, a personalized television news system. Upon visiting the EigenNews website, a user is shown a variety of news videos which have been automatically selected based on her individual preferences. These videos are extracted from 16 continually recorded television programs using a multimodal segmentation algorithm. Relevant metadata for each video are generated by linking videos to online news articles. Selected news videos can be watched in three different layouts and on various devices.

The proliferation of smart devices for mobile networks is a major traffic generator nowadays. These devices provide the ability to receive media content in nearly every situation. Despite that video streaming in high quality is getting more and more popular in mobile scenarios, the performance and bottlenecks of mobile applications over wireless networks, especially, during the transmission of media streams, are poorly understood yet. In order to tackle this new challenge, we present an Android based framework to capture the relevant wireless network behavior, geo-coordinates and packet traces for popular streaming applications on Android certified devices. A dataset has been obtained by measurement trials, which have been performed in a 3G network for both HTTP and peer-to-peer video streaming applications. The trials comprise also an additional WiFi measurement for comparison purposes. The presented dataset enables future research to determine the quality of service and network characteristics of different streaming methodologies, which are affected by the typical conditions encountered in wireless networks, like hand-over effects, signal fading, connection losses etc. We hope that both, the presented dataset and the framework, may prove to be useful for the traffic measurement and the multimedia research communities.

We propose a scenario-driven interactive panorama video delivery system that allows users to repeatedly watch the enjoyable parts of an event and share them with others. It provides functions for interactively watching panorama video parts, as well as for scenario making (with user-selected camera trajectory), and delivery that allows users to share their panorama watching experiences. In this technical demos, we demonstrate the system that can make a favorable and stable camera trajectories as a scenario from intuitive user manipulations of a tablet device in a format that can be easily shared with others.

We observe two trends, growing wireless capability at the physical layer powered by MIMO-OFDM, and growing video traffic as the dominant application traffic. Both the source and MIMO-OFDM channel components exhibit non-uniform energy distribution. This motivates us to leverage the source data redundancy at the channel to achieve high video recovery performance. We propose ParCast that first separates the source and channel into independent components, matches the more important source components with higher-gain channel components, allocates power weights with joint consideration to the source and the channel, and uses analog modulation for transmission. Such a scheme achieves fine-grained unequal error protection across source components. We implemented ParCast in Matlab and on Sora. Extensive evaluation shows that our scheme outperforms competitive schemes by notable margins, sometimes up to 5~dB in PSNR for challenging scenarios.

Due to the vast amount of video available in the Internet new access patterns emerge. Users do not always want to watch all of the content sequentially - such as in a movie - but want to pick specific parts, which are interesting for them. Based on a model of small and semantically meaningful and active video units, we derive an artificial hormone replication system that provides the flexibility for non-sequential access of units. We evaluate our model by simulation and compare it to a reference system. We show that simple local decisions contribute to global properties such as delay and robustness. We further introduce a clean-up function, which leads to adaptive management of the number of replicas.

In this demo, we present a working system that we have built for metadata-based compressed-domain spatio-temporal video adaptation of H.264/AVC videos. Our approach is in contrast to most existing approaches that do adaptation in a series of cascaded decode/re-encode procedures. We show that by applying compressed-domain operations, adaptation can be expedited for real-time application scenarios like news/sports broadcasting. Moreover, the system can be applied as a tool box for distributed adaptation within P2P video distribution applications to support heterogeneous devices.

Continuous media, such as digital movies, video clips, and music, are becoming an increasingly common way to present information, entertain and educate people. However, limited system and network resources have delayed the widespread usage of continuous media. In this paper, we propose a scalable and inexpensive video delivery paradigm, named Scheduled Video Delivery (SVD). In the SVD paradigm, users submit requests with specification of start time. The provider schedules these requests to meet the QoS specification and to maximize utilization of the resources. SVD scheduling has a different objective from many existing scheduling schemes. It does not aim at minimizing the waiting time. Instead, it focuses on meeting deadlines and at the same time combining requests to form multicasting groups. SVD scales not only to the number of users but also to the number of video objects.