Modern Internet streaming services have utilized various techniques to improve the quality of streaming media delivery. Despite the characterization of media access patterns and user behaviors in many measurement studies, few studies have focused on the streaming techniques themselves, particularly on the quality of streaming experiences they offer end users and on the resources of the media systems that they consume. In order to gain insights into current streaming services and thus provide guidance on designing resource-efficient and high quality streaming media systems, we have collected a large streaming media workload from thousands of broadband home users and business users hosted by a major ISP, and analyzed the most commonly used streaming techniques such as automatic protocol switch, Fast Streaming, MBR encoding and rate adaptation. Our measurement and analysis results show that with these techniques, current streaming systems tend to over-utilize CPU and bandwidth resources to provide better services to end users, which may not be a desirable and effective way to improve the quality of streaming media delivery. Motivated by these results, we propose and evaluate a coordination mechanism that effectively takes advantage of both Fast Streaming and rate adaptation to better utilize the server and Internet resources for streaming quality improvement.

Despite the growth in multimedia, there have been few studies that focus on characterizing streaming audio and video stored on the Web. This investigation used a customized Web crawler to traverse 17 million Web pages from diverse geographic locations and identify nearly 30,000 streaming audio and video clips available for analysis. Using custom-built extraction tools, these streaming media objects were analyzed to determine attributes such as media type, encoding format, playout duration, bitrate, resolution, and codec. The streaming media content encountered is dominated by proprietary audio and video formats with the top four commercial products being RealPlayer, Windows Media Player, MP3 and QuickTime. The distribution of the stored playout durations of streaming audio and video clips are long-tailed. More than half of the streaming media clips encountered are video, encoded primarily for broadband connections and at resolutions considerably smaller than the resolutions of typical monitors.

Abstract. Router queues can impact both round-trip times and throughput. Yet little is publicly known about queue provisioning employed by Internet services providers for the routers that control the access links to home computers. This paper proposes QFind, a black-box measurement technique, as a simple method to approximate the size of the access queue at last mile router. We evaluate QFind through simulation, emulation, and measurement. Although precise access queue results are limited by receiver window sizes and other system events, we find there are distinct difference between DSL and cable access queue sizes. 1

Abstract. The growth of wireless LANs has brought the expectation for high-bitrate streaming video to wireless PCs. However, it remains unknown how to best adapt video to wireless channel characteristics as they degrade. This paper presents results from experiments that stream commercial video over a wireless campus network and analyze performance across application, network and wireless link layers. Some of the key findings include: 1) Wireless LANs make it difficult for streaming video to gracefully degrade as network performance decreases; 2) Video streams with multiple encoding levels can more readily adapt to degraded wireless network conditions than can clips with a single encoding level; 3) Under degraded wireless network conditions, TCP streaming can provide higher video frame rates than can UDP streaming, but TCP streaming will often result in significantly longer playout durations than will UDP streaming; 4) Current techniques used by streaming media systems to determine effective capacity over wireless LAN are inadequate, resulting in streaming target bitrates significantly higher than can be effectively supported by the wireless network. 1

The increasing power and connectivity of today's computers have spurred the growth in streaming audio and video available on the Internet through the Web. While there is substantial research characterizing the performance of streaming media and characterizing documents stored on the Internet, there have been few studies characterizing streaming audio and video stored on the Web. We crawled over 17 million Web pages from key geographic locations and extracted nearly 30,000 streaming audio and video clips for analysis. Using custom built tools, we analyzed the characteristics of these multimedia objects, determining such information as media type, encoding format, playout duration, bitrate, resolution, and codec. We find proprietary audio and video from RealNetworks dominates all multimedia content, followed next by Microsoft and with Apple following just behind MP3. The playout durations of streaming audio and video clips are long-tailed, suggesting streaming media may contribute self-similar traffic on the Internet. More than half of all streaming media clips on the Internet are video, with 90% of videos targeted for broadband connections. Video resolutions are considerably smaller than typical monitor resolutions, implying that video bandwidths, which are directly related to resolutions, have enormous potential to increase. The detailed results from this study should be useful for future studies characterizing the performance of streaming media on the Internet and also valuable for those interested in generating more accurate Internet traffic simulations.

New TCP-Friendly constraints require multimedia flows to reduce their data rates under packet loss to that of a conformant TCP flow. To reduce data rates while preserving real-time playout, temporal scaling can be used to discard the encoded multimedia frames that have the least impact on perceived video quality. To limit the impact of lost packets, Forward Error Correction (FEC) can be used to repair frames damaged by packet loss. However, adding FEC requires further reduction of multimedia data, making the decision of how much FEC to use of critical importance. Current approaches use either inflexible FEC patterns or adapt to packet loss on the network without regard to TCP-Friendly data rate constraints. In this paper, we analytically model the playable frame rate of a TCP-Friendly MPEG stream with FEC and temporal scaling, capturing the impact of distributing FEC within MPEG frame types with interframe dependencies. For a given network condition and MPEG video encoding, we use our model to exhaustively search for the optimal combination of FEC and temporal scaling that yields the highest playable frame rate within TCP-Friendly constraints. Analytic experiments over a range of network and application conditions indicate that adjustable FEC with temporal scaling can provide a significant performance improvement over current approaches. Extensive simulation experiments based on Internet traces show that our model can be effective as part of a streaming protocol that chooses FEC and temporal scaling patterns that meet dynamically changing application and network conditions.

The repeated pattern of I, P and B frames in an MPEG stream is known as the Group of Pictures (GOP). Current GOP choices are made using intuition and informal guidelines without the support of theoretical or practical evidence. This paper studies the impact of the choice of GOP by evaluating the effects of GOP on both static MPEG videos and MPEG videos streaming over a lossy network. The static analysis involves encoding raw video images into MPEG files with various GOP patterns to compare and contrast static properties such as the frame size, file size and quality. The streaming analysis varies the GOP length and pattern to study the impact of GOP on a model of the streaming bitrate and playable frame rate. The results consistently suggest two guidelines: 1) the number of B frames between two reference frames should be close to 2, except when limited to less than 2 by time constraints; 2) the number of P frames should be 5 or fewer as there is little performance gain in setting the number of P frames in the GOP larger than 5.

Packet loss can severely impact streaming video quality. Repair techniques protect streaming video from packet loss but at the price of a reduced effective transmission rate when streaming a flow in a capacity constrained situation. This paper proposes an algorithm that optimizes the choice of Forward Error Correction (FEC) to repair packet loss for streaming MPEG videos under a capacity constraint with quality scaling. An analytic model is developed to estimate the video quality of streaming MPEG given a quality scaling level and a specific FEC strength. Given network conditions in terms of packet loss rate, the model searches the total variable space to find the combination of FEC and scaling that yields the optimal quality under the capacity constraint. Analysis over a range of network conditions indicates that adjusting FEC with quality scaling provides significant performance improvement.

Streaming multimedia quality is impacted by two main factors: capacity constraint and packet loss. To match the capacity constraint while preserving real-time playout, media scaling can be used to discard the encoded multimedia content that has the least impact on perceived video quality. To limit the impact of lost packets, repair techniques, e.g. forward error correction (FEC), can be used to repair frames damaged by packet loss. However, adding data to facilitate repair requires further reduction of the original multimedia data, making the decision of how much repair data to use of critical importance. Assuming a limited network capacity and the availability of an estimate of the current packet loss rate along a flow path, selecting the best distribution of FEC packets for video frames with inherent interframe encoding dependencies can be cast as a constraint optimization problem that attempts to optimize the quality of the video stream. This thesis presents an Adjusting Repair and Media scaling with Operations

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