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

Buffer management for scalable video streaming

In a video streaming scenario, to cope with bandwidth variations, buffer management and intelligent drop packets policies play a critical role in the final quality of the video received at the user side. In this context, we present a buffer management strategy implemented at the source of a video communication system. This scheme uses priority information from the H.264/SVC encoder, network information from a Bandwidth Estimation approach (BE), based on Hidden Markov Model (HMM) and monitors buffer fullness: when it exceeds a defined threshold, the selective discard strategy takes place. To get more flexibility, we employed SNR quality scalability (Medium Grain Scalability), to get more than one rate point for each enhancement layer. Low priority packets correspond to higher quality layers and are discarded first, with the aim to preserve as much as possible more relevant lower layer packets. Dependencies created by the encoding process are kept into account. We show that the strategy presented ensures that the video transmitted has the highest possible quality under the given network conditions and buffer resources

Buffer management for scalable video streaming

In a video streaming scenario, to cope with bandwidth variations, buffer management and intelligent drop packets policies play a critical role in the final quality of the video received at the user side. In this context, we present a buffer management strategy implemented at the source of a video communication system. This scheme uses priority information from the H.264/SVC encoder, network information from a Bandwidth Estimation approach (BE), based on Hidden Markov Model (HMM) and monitors buffer fullness: when it exceeds a defined threshold, the selective discard strategy takes place. To get more flexibility, we employed SNR quality scalability (Medium Grain Scalability), to get more than one rate point for each enhancement layer. Low priority packets correspond to higher quality layers and are discarded first, with the aim to preserve as much as possible more relevant lower layer packets. Dependencies created by the encoding process are kept into account. We show that the strategy presented ensures that the video transmitted has the highest possible quality under the given network conditions and buffer resources

Buffer management for scalable video streaming

In a video streaming scenario, to cope with bandwidth variations, buffer management and intelligent drop packets policies play a critical role in the final quality of the video received at the user side. In this context, we present a buffer management strategy implemented at the source of a video communication system. This scheme uses priority information from the H.264/SVC encoder, network information from a Bandwidth Estimation approach (BE), based on Hidden Markov Model (HMM) and monitors buffer fullness: when it exceeds a defined threshold, the selective discard strategy takes place. To get more flexibility, we employed SNR quality scalability (Medium Grain Scalability), to get more than one rate point for each enhancement layer. Low priority packets correspond to higher quality layers and are discarded first, with the aim to preserve as much as possible more relevant lower layers packets. Dependencies created by the encoding process are kept into account. We show that the strategy presented ensures that the video transmitted has the highest possible quality under the given network conditions and buffer resources

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Video streaming in a best effort network, where bandwidth availability fluctuates over time, is one of the most challenging in the multimedia research field. Bandwidth fluctuation leads to a variation in the delay of the video flow and therefore degradation of the quality of experience (QOE). To tolerate variations in instantaneous bandwidth, the scalable video codec (SVC) an extension of the H.264/AVC was designed. This paper presents the weighted multi-playback buffer management system for scalable video streaming in a congested network. The approach intrinsically provides weighted protection to the more important video layers within a video stream. We compare the performance of our weighted scheme with a multi-playback buffer which gives equal protection to every video layer. The simulation results show that weighted multi-playback buffer management can improve the average Y-PSNR and the continuity of the SVC video stream

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