Measurement And Improvement of Quality-of-Experience For Online Video Streaming Services

Title from PDF of title page, viewed on September 4, 2015Dissertation advisor: Deep MedhiVitaIncludes bibliographic references (pages 126-141)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2015HTTP based online video streaming services have been consistently dominating the online traffic for the past few years. Measuring and improving the performance of these services is an important challenge. Traditional Quality-of-Service (QoS) metrics such as packet loss, jitter and delay which were used for networked services are not easily understood by the users. Instead, Quality-of-Experience (QoE) metrics which capture the overall satisfaction are more suitable for measuring the quality as perceived by the users. However, these QoE metrics have not yet been standardized and their measurement and improvement poses unique challenges. In this work we first present a comprehensive survey of the different set of QoE metrics and the measurement methodologies suitable for HTTP based online video streaming services. We then present our active QoE measurement tool Pytomo that measures the QoE of YouTube videos. A case study on the measurement of QoE of YouTube videos when accessed by residential users from three different Internet Service Providers (ISP) in a metropolitan area is discussed. This is the first work that has collected QoE data from actual residential users using active measurements for YouTube videos. Based on these measurements we were able to study and compare the QoE of YouTube videos across multiple ISPs. We also were able to correlate the QoE observed with the server clusters used for the different users. Based on this correlation we were able to identify the server clusters that were experiencing diminished QoE. DynamicAdaptive Streaming overHTTP (DASH) is an HTTP based video streaming that enables the video players to adapt the video quality based on the network conditions. We next present a rate adaptation algorithm that improves the QoE of DASH video streaming services that selects the most optimum video quality. With DASH the video server hosts multiple representation of the same video and each representation is divided into small segments of constant playback duration. The DASH player downloads the appropriate representation based on the network conditions, thus, adapting the video quality to match the conditions. Currently deployed Adaptive Bitrate (ABR) algorithms use throughput and buffer occupancy to predict segment fetch times. These algorithms assume that the segments are of equal size. However, due to the encoding schemes employed this assumption does not hold. In order to overcome these limitations, we propose a novel Segment Aware Rate Adaptation algorithm (SARA) that leverages the knowledge of the segment size variations to improve the prediction of segment fetch times. Using an emulated player in a geographically distributed virtual network setup, we compare the performance of SARA with existing ABR algorithms. We demonstrate that SARA helps to improve the QoE of the DASH video streaming with improved convergence time, better bitrate switching performance and better video quality. We also show that unlike the existing adaptation schemes, SARA provides a consistent QoE irrespective of the segment size distributions.Introduction -- Measurement of QoE for Online Video Streaming Services: A Literature Survey -- Pytomo: A Tool for measuring QoE of YouTube Videos -- Case Study: QoE across three Internet Service Providers in a Metropolitan Area -- Adaptive Bitrate Algorithms for DASH -- Segment Aware Rate Adaptation for DASH -- Performance Evaluation of SARA -- Conclusion and Future Research --Appendix A. Sample MPD Fil

Improving Content Delivery and Service Discovery in Networks

Production and consumption of multimedia content on the Internet is rising, fueled by the demand for content from services such as YouTube, Netflix and Facebook video. The Internet is shifting from host-based to content-centric networking. At the same time, users are shifting away from a homogeneous desktop computing environment to using a heterogeneous mix of devices, such as smartphones, tablets and thin clients, all of which allow users to consume data on the move using wireless and cellular data networks. The popularity of these new class of devices has, in turn, increased demand for multimedia content by mobile users. The emergence of rich Internet applications and the widespread adoption and use of High Definition (HD) video has also placed higher pressure on the service providers and the core Internet backbone, forcing service providers to respond to increased bandwidth use in such networks. In my thesis, I aim to provide clarity and insight into the usage of core networking protocols and multimedia consumption on both mobile and wireless networks, as well as the network core. I also present research prototypes for potential solutions to some of the problems caused by the increased multimedia consumption on the Internet

Understanding the performance of Internet video over residential networks

Video streaming applications are now commonplace among home Internet users, who typically access the Internet using DSL or Cable technologies. However, the effect of these technologies on video performance, in terms of degradations in video quality, is not well understood. To enable continued deployment of applications with improved quality of experience for home users, it is essential to understand the nature of network impairments and develop means to overcome them. In this dissertation, I demonstrate the type of network conditions experienced by Internet video traffic, by presenting a new dataset of the packet level performance of real-time streaming to residential Internet users. Then, I use these packet level traces to evaluate the performance of commonly used models for packet loss simulation, and finding the models to be insufficient, present a new type of model that more accurately captures the loss behaviour. Finally, to demonstrate how a better understanding of the network can improve video quality in a real application scenario, I evaluate the performance of forward error correction schemes for Internet video using the measurements. I show that performance can be poor, devise a new metric to predict performance of error recovery from the characteristics of the input, and validate that the new packet loss model allows more realistic simulations. For the effective deployment of Internet video systems to users of residential access networks, a firm understanding of these networks is required. This dissertation provides insights into the packet level characteristics that can be expected from such networks, and techniques to realistically simulate their behaviour, promoting development of future video applications

QoE Evaluation Across a Range of User Age Groups in Video Applications

PhDQuality of Service (QoS) measures are the network parameters; delay, jitter, and loss and they do not reflect the actual quality of the service received by the end user. To get an actual view of the performance from a user’s perspective, the Quality of the Experience (QoE) measure is now used. Traditionally, QoS network measurements are carried on actual network components, such as the routers and switches since these are the key network components. In this thesis, however, the experimentation has been done on real video traffic. The experimental setup made use of a very popular network tool, Network Emulator (NetEm) created by the Linux Foundation. NetEm allows network emulation without using the actual network devices such as the routers and traffic generator. The common NetEm offered features are those that have been used by the researchers in the past. These have the same limitation as a traditional simulator, which is the inability of NetEm delay jitter model to represent realistic network traffic models, such to reflect the behaviour of real world networks. The NetEm default method of inputting delay and jitter adds or subtracts a fixed amount of delay on the outgoing traffic. NetEm also allows the user to add this variation in a correlated fashion. However, using this technique the outputted packet delays are generated in such a way as to be very limited and hence not much like real internet traffic which has a vast range of delays. The standard alternative that NetEm allows is generate the delays from either a Normal (Gaussian) or Pareto distribution. This research, however, has shown that using a Gaussian or Pareto distribution also has very severe limitations, and these are fully discussed and described in Chapter 5 on page 68 of this thesis. This research adopts another approach that is also allowed (with more difficulty) by NetEm: by measuring a very large number of packet delays generated from a double exponential distribution a packet delay profile is created that far better imitates the actual delays seen in Internet traffic. In this thesis a large set of statistical delay values were gathered and used to create delay distribution tables. Additionally, to overcome another default behaviour of NetEm of re-ordering packets once jitter is implemented, PFIFO queuing discipline has been deployed to retain the original packet order regardless of the highest levels of implemented jitter. Furthermore, this advancement in NetEm’s functionality also incorporates the ability to combine delay, jitter, and loss, which is not allowed on NetEm by default. In the literature, no work has been found to have utilised NetEm previously with such an advancement. Focusing on Video On Demand (VOD) it was discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. A bottleneck TCP model was then used to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required. The results are potentially very useful to service providers and network designers to be able to provide a satisfactory service to their customers, and in return, maintaining a prosperous business.EPSRC (1589943)

Factors influencing the popularity of YouTube videos and users’ decisions to watch them

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.YouTube has substantial impact on modern society as the second most popular website in the world. Despite its sustained popularity, little is known about which types of video are most viewed and the reasons why people choose to watch them. This research critically analyses the sample of videos provided by the YouTube API, then uses the metrics associated with these videos to help assess which types of YouTube video are popular. It also harnesses a questionnaire of mainly UK teacher education graduate YouTube users to investigate which factors influence decisions to watch YouTube videos. This was a convenience sample selected to achieve a high response rate, which it achieved (81%), minimising non-response bias. The video lists provided by the YouTube API were not random samples but contained a wide range of types of video (including both popular and unpopular), except that older videos were avoided. There were substantial differences between categories in the average properties of the videos returned and the proportion of videos returned on multiple days. The most popular categories from the YouTube metadata collected based on average view counts are varied: From TV, Best of, Animation and How-to. Cause-based video categories tended to be unpopular. Video popularity did not seem to be affected by video duration, on average. Users are more likely to interact with (comment, like, dislike) videos that are useful or supporting in some way. Videos that are interacted with more are not always more popular, with subject content affecting this relationship. In addition, high view counts associated with fewer likes, dislikes and comments per view, suggesting that indicators of popularity may not attract new viewers. The most popular categories with survey respondents were slightly different, partly reflecting their educational background (e.g., Education videos), and there were some (stereotypical) gender differences in the most popular categories. Respondents rarely believed that they were influenced by a video’s popularity or evidence of other users’ reactions to it when deciding to watch the video. Instead, they were most likely to be influenced by content-related factors, such as a video’s title and thumbnail picture. Despite previous research showing that people can be influenced by the opinions and watching habits of others, respondents claimed to be little influenced by this. Nevertheless, they frequently reported watching videos posted to Facebook, possibly trusting the person that posted the video. Thus, despite extensive discussion of various forms of viral information spreading, content, rather than popularity, is king in YouTube, although online word-of-mouth sharing through trusted relationships is also important. The main limitations of this research are that the data used may not be representative of YouTube and all UK YouTube users overall, so the conclusions should be interpreted cautiously

How Do You Tube? : tärykalvoputkituksen simulaatiomallit

Tämä tutkielma käsittelee tärykalvoputkitusta ja siihen liittyen selvitettiin, millä tavalla HUS korva-, nenä- ja kurkkutautien poliklinikalla työskentelevät erikoislääkärit ja erikoistumisjaksoaan suorittavat lääkärit putkittavat tärykalvon ja miten tärykalvoputkitusta voidaan harjoitella. Samalla tutkielma esittelee tutkimuksessa käytetyn tärykalvoputkitukseen soveltuvan harjoitusmallin, jota aloitteleva korva-, nenä- ja kurkkutaudeille erikoistuva lääkäri voi käyttää harjoitellakseen tärykalvoputkitusta ennen ensimmäisiä leikkauksiaan. Putkitustavassa olemme kiinnostuneet siitä, putkittavatko kaikki lääkärit samalla tavalla vai tuleeko putkituksissa eroavaisuuksia. Tavoitteena on, että mikäli kaikki putkittaisivat tärykalvot samalla tavalla, voisimme antaa leikkausta avustaville henkilöille ohjeita siitä, miten leikkaukseen voidaan valmistautua instrumenttien ym. osalta paremmin