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An adaptive, cross layer error control scheme for Distributed Video Coding over Wireless Multimedia Sensor Networks

机译:用于无线多媒体传感器网络的分布式视频编码的自适应跨层误差控制方案

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Distributed Video Coding with low computational complexity at the encoder side has a high potential for use in Wireless Multimedia Sensor Networks. However, the different architecture of this coding and resource constraints in WMSNs require the design of new efficient transmission protocols for transmission of DVC through WMSNs. In view of these protocols, error control mechanisms have more importance in reliable multimedia communication over WMSN. These mechanisms provide higher video quality in receiver nodes while saving the energy of sender nodes by the reliable transmission of packets. Given the importance of this issue, in this paper, we propose an adaptive, cross-layer error control scheme to protect video frames in the transmission of DVC over WMSN, which serves QOS while considering energy consumption and frames' delay constraints. To propose this scheme, we used the accurate results from our previous works on error resiliency of DVC and comparative performance analysis of error control methods for this codec. The proposed scheme has been analyzed and compared to all standard, layer and, multi-layer error control schemes against the most important criteria in video communication over WSNs such as energy consumption, delay, and PSNR. Simulation results show that this scheme saves the quality of video in different channel conditions by consuming the least possible amount of energy based on the maximum allowable delay at the receiver.
机译:在编码器侧的低计算复杂度具有低计算复杂度的分布式视频编码具有很高的无线多媒体传感器网络的可能性。然而,WMSNS中该编码和资源约束的不同架构需要设计用于通过WMSNS传输DVC的新高效传输协议。鉴于这些协议,错误控制机制在WMSN上的可靠多媒体通信中具有更多重要性。这些机制在接收器节点中提供更高的视频质量,同时通过可靠的分组传输节省发件人节点的能量。鉴于本问题的重要性,在本文中,我们提出了一种自适应,跨层错误控制方案来保护视频帧在DVC上通过WMSN传输,这在考虑能量消耗和帧延迟约束的同时提供QoS。为提出此计划,我们使用我们之前的工作中的准确结果对DVC的误差弹性以及该编解码器的错误控制方法的比较性能分析。已经分析了该方案,并与所有标准,层和多层错误控制方案进行了分析,并与WSN上的视频通信中最重要的标准进行了比较,例如能量消耗,延迟和PSNR。仿真结果表明,该方案通过消耗基于接收器处的最大允许延迟消耗最小可能的能量来节省不同信道条件中的视频质量。

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