Scalable Video Coding of H.264/AVC Video Streaming with QoS-based Active Dropping in 802.16e networks

[[abstract]]Multimedia applications over mobile wireless network are becoming popular in recent years. High video quality depends on the wide bandwidth but the wide bandwidth restricts the number of users in the network system. Effective bandwidth utilization is the major problem in wireless network because the bandwidth resource in wireless environment is limited and precious. For this reason, we propose an active dropping mechanism to deal with the effective bandwidth utilization problem. In the proposed mechanism, if the network loading exceeds the threshold, the dropping mechanism starts to drop the enhancement layer data for low level user and the dropping probability is varying with the different network loading. For the multimedia application, we use the characteristic of the scalable video coding (SVC) extension of H.264/AVC standard to provide different video quality for different level user. By the dropping mechanism, base station increases the system capability and users can obtain better quality of service when the system is under heavy loading. In this paper, we study the network platform of the 802.16e standard and add the QoS-based active dropping mechanism to the MAC layer. In the simulation results, the system capability that releases bandwidth by dropping mechanism and service quality of users are observed.[[conferencetype]]國際[[conferencedate]]20080325~20080328[[booktype]]紙本[[conferencelocation]]Okinawa, Japa

Congestion-Aware Scalable Video Streaming

Postprin

Cross-layer H.264 scalable video downstream delivery over WLANs

Thanks to its in-network drop-based adaptation capabilities, H.264 Scalable Video Coding is perceived as an effective approach for delivering video over networks characterized by sudden large bandwidth fluctuations, such as Wireless LANs. Performance may be boosted by the adoption of application-aware/cross-layer schedulers devised to intelligently drop video data units (NALUs), so that i) decoding dependencies are preserved, and ii) the quality perceived by the end users is maximized. In this paper, we provide a theoretical formulation of a QoE utility-optimal cross-layer scheduling problem for H.264 SVC downlink delivery over WLANs. We show that, because of the unique characteristics of the WLAN MAC operation, this problem significantly differs from related approaches proposed for scheduled wireless technologies, especially when the WLAN carries background traffic in the uplink direction. From these theoretical insights, we derive, design, implement and experimentally assess a simple practical scheduling algorithm, whose performance is very close to the optimal solution

Employing H.264 Coarse and Medium Grain Scalable Video to Optimize Video Playback over Passive Optical Networks

In this work, we propose the use of Coarse Grain Scalable (CGS) and Medium Grain Scalable (MGS) H.264/AVC video to optimize video playback on passive optical networks (PONs) by investigating network performance metrics such as data delay, video delay, and video delay jitter. Video playback is improved by sequentially dropping layers of scalable video. Dropping just a single CGS enhancement layer results in improvements of up to 57% for both data and video delay. However, video delay jitter benefits the most with an improvement ranging from 47% to 87%. Surprisingly, dropping subsequent CGS enhancement layers does not significantly improve the PONs performance. In order to remedy this effect, our focus switched to employing the H.264/AVC MGS video standard. Though video traffic delay is the primary object of optimization in this work, the proposed algorithm’s impacts on other network performance metrics such as data traffic delay and video traffic delay variance (jitter) are analyzed as well. Video playback is improved by employing an adaptive scalable video layer dropping algorithm which drops a progressively larger number of scalable video layers as network utilization increases as measured by the moving average of the video packet delay. The influence of the algorithm\u27s three parameters on its performance is investigated in detail, and the results of the optimized adaptive dropping algorithm are compared to baseline static dropping algorithm

Adaptive Live Video Streaming by Priority Drop

In this paper we explore the use of Priority-progress streaming (PPS) for video surveillance applications. PPS is an adaptive streaming technique for the delivery of continuous media over variable bit-rate channels. It is based on the simple idea of reordering media components within a time window into priority order before transmission. The main concern when using PPS for live video streaming is the time delay introduced by reordering. In this paper we describe how PPS can be extended to support live streaming and show that the delay inherent in the approach can be tuned to satisfy a wide range of latency constraints while supporting fine-grain adaptation