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

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Abstract

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.

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Authors and Affiliations

  1. Faculty of Computer Science, Kateb University, Kabul, Afghanistan

    Mortaza Nikzad

  2. Faculty of Computer Engineering, University of Isfahan, Isfahan, Iran

    Ali Bohlooli & Kamal Jamshidi

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  1. Mortaza Nikzad
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  2. Ali Bohlooli
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  3. Kamal Jamshidi
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Correspondence to Ali Bohlooli.

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Nikzad, M., Bohlooli, A. & Jamshidi, K. An adaptive, cross layer error control scheme for Distributed Video Coding over Wireless Multimedia Sensor Networks. Multimed Tools Appl 79, 32999–33021 (2020). https://doi.org/10.1007/s11042-020-09594-y

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