Adaptive and ubiquitous video streaming over Wireless Mesh Networks

Abstract

International audienceIn recent years, with the dramatic improvement on scalability of H.264/MPEG-4 standard and growing demand for new multimedia services have spurred the research on scalable video streaming over wireless networks in both industry and academia. Video streaming applications are increasingly being deployed in Wireless Mesh Networks (WMNs). However, robust streaming of video over WMNs poses many challenges due to varying nature of wireless networks. Bit-errors, packet-losses and burst-packet-losses are very common in such type of networks, which severely influence the perceived video quality at receiving end. Therefore, a carefully-designed error recovery scheme must be employed. In this paper, we propose an interactive and ubiquitous video streaming scheme for Scalable Video Coding (SVC) based video streaming over WMNs towards heterogeneous receivers. Intelligently taking the benefit of path diversity, the proposed scheme initially calculates the quality of all candidate paths and then based on quality of path it decides adaptively the size and level of error protection for all packets in order to combat the effect of losses on perceived quality of reconstructed video at receiving end. Our experimental results show that the proposed streaming approach can react to varying channel conditions with less degradation in video quality

Optimization of Video Transmission Quality in Wireless Networks

“…Numerous approaches have been suggested to address the demands of secure video communication over noisy channels. These solutions encompass techniques such as Adaptive Modulation (AM), Forward Error Correction (FEC), Automatic Repeat Request (ARQ), Joint Source-Channel Coding (JSCC) for retransmission, robust source coding, adaptive channelsource coding, data partitioning, post-processing error concealment, and scalable transportpriority coding [12][13][14][15].…”

Multimedia Real-Time Transmission Protocol and Its Application in Video Transmission System

“…Meng and others pointed out bandwidth estimation and bit rate selection as they are the core of the client-side bit rate adaptive algorithm and used Q learning enhanced learning algorithm to train a decision-making Q matrix; according to the current network status and buffer saturation, the Q matrix is referred to determine an action that can obtain the maximum return value; the algorithm can achieve higher bit rate level, less bit rate switching time, and balance the amount of buffered data [ 9 ]. Hassan and others used historical download data to predict the network bandwidth in the next stage, using the standard deviation method; replaced the original SF algorithm for the calculation of volatility parameters [ 10 ]; made the bandwidth prediction result smoother and slow down the occurrence of the “burr” phenomenon, and combined with the buffer management strategy to make the basis for the code rate decision, avoiding the shortcomings of relying on a single parameter as the code rate selection. The algorithm has high stability, but when the state of the cache is in the balance zone, even if the available bandwidth resources of the network become larger, the algorithm pursues stability.…”

Low Complexity for Scalable Video Coding Extension of H.264 based on the Complexity of Video

“…The BL represents the main information of the video and should be transmitted with very high reliability [4]. On the other hand, the EL sent part of a bit stream according to the destination required [5].…”