The recently developed H.264/AVC video codec with Scalable Video Coding (SVC) extension, compresses non-scalable (single-layer) and scalable video significantly more efficiently than MPEG–4 Part 2. Since the traffic characteristics of encoded video have a significant impact on its network transport, we examine the bit rate-distortion and bit rate variability-distortion performance of single-layer video traffic of the H.264/AVC codec and SVC extension using long CIF resolution videos. We also compare the traffic characteristics of the hierarchical B frames (SVC) versus classical B frames. In addition, we examine the impact of frame size smoothing on the video traffic to mitigate the effect of bit rate variabilities. We find that compared to MPEG–4 Part 2, the H.264/AVC codec and SVC extension achieve lower average bit rates at the expense of significantly increased traffic variabilities that remain at a high level even with smoothing. Through simulations we investigate the implications of this increase in rate variability on (i) frame losses when transmitting a single video, and (ii) on the number of supported video streams in a bufferless statistical multiplexing scenario with restricted link capacity and information loss. We find increased frame losses, and rate-distortion/rate-variability/encoding complexity tradeoffs. We conclude that solely assessing bit rate-distortion improvements of video encoder technologies is not sufficient to predict the performance in specific networked application scenarios. Index Terms Frame loss ratio, H.264/AVC, hierarchical B frames, rate-distortion (RD), rate variability-distortion (VD), single-layer video, statistical multiplexing, SVC, video traffic. I.

Extracting performance from modern parallel architectures requires that applications be divided into many different threads of execution. Unfortunately selecting the appropriate number of threads for an application is a daunting task. Having too many threads can quickly saturate shared resources, such as cache capacity or memory bandwidth, thus degrading performance. On the other hand, having too few threads makes inefficient use of the resources available. Beyond static resource assignment, the program inputs and dynamic system state (e.g., what other applications are executing in the system) can have a significant impact on the right number of threads to use for a particular application. To address this problem we present the Thread Tailor, a dynamic system that automatically adjusts the number of threads in an application to optimize system efficiency. The Thread Tailor leverages offline analysis to estimate what type of threads will exist at runtime and the communication patterns between them. Using this information Thread Tailor dynamically combines threads to better suit the needs of the target system. Thread Tailor adjusts not only to the architecture, but also other applications in the system, and this paper demonstrates that this type of adjustment can lead to significantly better use of thread-level parallelism in real-world architectures.

content such as news or sports updates. However, mobile wireless networks typically suffer from severe bandwidth fluctuations, and the networks are often completely unresponsive for several seconds, sometimes minutes. Today, there are several ways of adapting the video bitrate and thus the video quality to such fluctuations, e.g., using scalable video codecs or segmented adaptive HTTP streaming that switches between non-scalable video streams encoded in different bitrates. Still, for a better long-term video playout experience that avoids disruptions and frequent quality changes while using existing video adaptation technology, it is desirable to perform bandwidth prediction and planned quality adaptation. This paper describes a video streaming system for receivers equipped with a GPS. A receiver’s download rate is constantly monitored, and periodically reported back to a central database along with associated GPS positional data. Thus, based on the current location, a streaming device can use a GPS-based bandwidth-lookup service in order to better predict the near-future bandwidth availability and create a schedule for the video playout that takes likely future availability into account. To create a prototype and perform initial tests, we conducted several field trials while commuting using public transportation. We show how our database has been used to predict bandwidth fluctuations and network outages, and how this information helps maintain uninterrupted playback with less compromise on video quality than possible without prediction.

The High-Speed Downlink Packet Access (HSDPA) communication protocol improves downlink performance on mobile networks and is currently being deployed in networks around the world. In Norway, two operators started offering this service in 2007. This article discusses performance measurements done in Telenor’s HSDPA network in Oslo in the context of video streaming. In particular, we present the results of streaming experiments measuring characteristics such as packet loss, latency, jitter and bit-errors. Based on this data, we evaluate the HSDPA network’s suitability for real-time video streaming, and discuss what can be done to improve the quality of video streaming under the observed network characteristics. 1.

Advances in hardware capacity, especially I/O devices such as cameras and displays, are driving the development of applications like high-definition video conferencing that have tight timing and CPU requirements. Unfortunately, current operating systems do not adequately provide the timing response needed by these applications. In this paper, we present a hierarchical scheduling model that aims to provide these applications with tight timing response, while at the same time preserve the strengths of current schedulers, namely fairness and efficiency. Our approach, called cooperative polling, consists of an application-level event scheduler and a kernel thread scheduler that cooperate to dispatch time-constrained application events accurately and with minimal kernel preemption, while still ensuring rigorously that all applications share resources fairly. Fairness is enforced in a flexible manner, allowing sharing according to a mixture of both traditional resource-centric metrics and new application-centric metrics, the latter being critical to support graceful application-level adaptation in overload. Unlike traditional real-time systems, our model does not require specification or estimation of resource requirements, simplifying its usage dramatically. Our evaluation, using an adaptive video application and a graphics server, shows that our system has event dispatch accuracies that are one to two orders of magnitude smaller than are achieved by existing schedulers. At the same time, our scheduler still maintains fairness and has low overhead.

Abstract — With the increased popularity of mobile multimedia services, efficient and robust video multicast strategies are of critical importance. In a conventional multicast system, the source station transmits at the base rate of the underlying network so that all the nodes can receive the data correctly. The performance of such a multicast system is limited by the node with the worst channel conditions, which usually corresponds to the nodes at the edge of the multicast coverage range. To overcome this problem, we propose a two-hop cooperative transmission scheme where in the first hop the source station transmits the packets and the nodes who receive the packets forward the packets simultaneously in the second hop using Randomized Distributed Space Time Codes (R-DSTC). We further integrate this randomized cooperative transmission with layered video coding to provide users different video quality based on their channel conditions. The performance of the system is evaluated and compared with a conventional multicast system. Our results show that the proposed cooperative system significantly improves the performance compared to conventional multicast. Index Terms: layered video coding, user cooperation, randomized distributed space time coding, wireless networks, video multicast I.

Abstract—Layered streaming can be used to adapt to the available download capacity of an end-user, and such adaptation is very much required in real world HTTP media streaming. The multiple layer codec has become more refined, as SVC (the scalable extension of the H.264/AVC standard) has been standardized with a bit rate overhead of around 10 % and an indistinguishable visual quality, compared to the state of the art single layer codec. Peer-to-peer streaming systems have also become the reality. The important question is how such layered coding can be used in real world peer-to-peer streaming systems. This paper tries to explore the feasibility of using network coding to make layered peer-to-peer streaming much more realistic, by combining network coding and SVC in a fine granularity manner. We present Chameleon, our new peer-to-peer streaming algorithm designed to incorporate network coding seamlessly with SVC. Key components with different design options of Chameleon are presented and experimentally evaluated, with the objective of investigating benefits of network coding in combination with SVC. We carry out extensive experiments on real stream data to (i) evaluate the performance of Chameleon in terms of playback skips and delivered video quality, and (ii) understand its insights. Our results demonstrate the feasibility of the approach and bring us one step closer to real adaptive peer-to-peer streaming. I.

Abstract — With the fast-paced development of computing technologies, mobile devices have almost sufficient computation and communication capabilities to support mobile multimedia applications such as multimedia streaming, VoIP, and mobile TV. However, most existing mobile devices are powered by battery with limited energy resource. To support multimedia on battery-powered mobile devices, how to efficiently utilize the limited power source and other limited network resources has become one of the major challenges in mobile multimedia system design. It has been shown that achieving a satisfactory user experience needs a systematic consideration of both video source adaptation and network transmission adaptation, indicating that the core of mobile multimedia system design is how to achieve a good balance of the power consumption between computation usage and communication usage. In other words, it depends on how to jointly select video source parameters and channel parameters based on the video content characteristics, available network resources, and underlying network conditions, given the fact that the power management schemes as well as the nonlinear battery effects also affect the system power consumption of mobile devices. In this paper, we review the recent advances in power-aware mobile multimedia, especially the adaptation technologies applied in video coding and delivery. In addition, the major research challenges in the field are demonstrated and discussed, which include power-management for mobile devices, rate-distortion-complexity optimized video codec design, and computational complexity and power aware cross-layer design and optimization. At the end, we propose a number of future research directions for audiences to continue investigation in this field. Index Terms — Power-aware multimedia, H.264, power management, joint source-channel coding, power adaptation, cross-layer design and optimization I.

Abstract—The newly adopted scalable extension of H.264/AVC video coding standard (SVC) demonstrates significant improvements in coding efficiency in addition to an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. Due to the complicated hierarchical prediction structure of the SVC and the concept of key pictures, content-aware rate adaptation of SVC bit streams to intermediate bit rates is a nontrivial task. The concept of quality layers has been introduced in the design of the SVC to allow for fast content-aware prioritized rate adaptation. However, existing quality layer assignment methods are suboptimal and do not consider all network abstraction layer (NAL) units from different layers for the optimization. In this paper, we first propose a technique to accurately and efficiently estimate the quality degradation resulting from discarding an arbitrary number of NAL units from multiple layers of a bitstream by properly taking drift into account. Then, we utilize this distortion estimation technique to assign quality layers to NAL units for a more efficient extraction. Experimental results show that a significant gain can be achieved by the proposed scheme. I.

Abstract — Peer-to-peer (P2P) networks represent a valuable architecture for streaming video over the Internet. In these systems, users contribute their resources to relay the media to others and no dedicated infrastructure is required. In order to ensure a low end-to-end delay, P2P overlay networks are often organized as a set of complementary multicast trees. The source of the stream multiplexes the data on top of these trees and the routing of packets is statically defined. In this scenario, the reliability of the overlay links is critical for the performance of the system since temporary link failure or network congestion can cause a significant disruption of the end-user quality. The novel Scalable Video Coding (SVC) standard enables efficient usage of the network capacity by allowing intermediate high capacity nodes in the overlay network to dynamically extract layers from the scalable bit stream to serve less capable peers. On the other hand, SVC incurs a certain loss in terms of coding efficiency with respect to H.264/AVC single-layer coding. We propose a simple model that allows to evaluate the trade-off of using a scalable codec with respect to single-layer coding, given the distribution of the receivers ’ capacities in an error-free network. We also report experimental results obtained by using SVC on top of a real-time implementation of the Stanford Peer-to-Peer Multicast (SPPM) protocol that clearly show the benefits of a prioritization mechanism to react to network congestion. I.