Optimization of System Performance for DVC Applications with Energy Constraints over Ad Hoc Networks

We investigate optimization of system performance in the below scenario: capturing and transmitting videos by single or multiple video sensors using distributed video coding (DVC) over ad hoc networks. There is an intrinsic contradiction in this scenario that could affect the system performance: the contradiction between the decoding quality and network lifetime. In this paper, we propose a joint optimization between the decoding quality and network lifetime using a quantitative metric of system performance, which is defined as the amount of collected visual information during the operational time of the video sensor. Based on the proposed metric, an optimal encoding rate is determined, which results in an optimal system performance. The simulation results show that the optimal encoding rate can be determined to achieve the optimal system performance.

[1]  Ishfaq Ahmad,et al.  Power-rate-distortion analysis for wireless video communication under energy constraint , 2004, IS&T/SPIE Electronic Imaging.

[2]  Ishfaq Ahmad,et al.  Power-rate-distortion analysis for wireless video communication under energy constraints , 2005, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Rui Zhang,et al.  Wyner-Ziv coding of motion video , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[4]  Aaron D. Wyner,et al.  Recent results in the Shannon theory , 1974, IEEE Trans. Inf. Theory.

[5]  Aaron D. Wyner,et al.  The rate-distortion function for source coding with side information at the decoder , 1976, IEEE Trans. Inf. Theory.

[6]  Bernd Girod,et al.  Distributed Video Coding , 2005, Proceedings of the IEEE.

[7]  Bernd Girod,et al.  Generalization of the rate-distortion function for Wyner-Ziv coding of noisy sources in the quadratic-Gaussian case , 2005, Data Compression Conference.

[8]  Kannan Ramchandran,et al.  Distributed source coding using syndromes (DISCUSS): design and construction , 1999 .

[9]  Rui Zhang,et al.  Wyner-Ziv coding for video: applications to compression and error resilience , 2003, Data Compression Conference, 2003. Proceedings. DCC 2003.

[10]  Wendi Heinzelman,et al.  Energy-efficient communication protocol for wireless microsensor networks , 2000, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences.

[11]  Wu-chi Feng,et al.  Panoptes: scalable low-power video sensor networking technologies , 2003, ACM Multimedia.

[12]  K. Ramchandran,et al.  Distributed source coding using syndromes (DISCUS): design and construction , 1999, Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096).

[13]  Jack K. Wolf,et al.  Noiseless coding of correlated information sources , 1973, IEEE Trans. Inf. Theory.

[14]  Zhihai He,et al.  Accumulative visual information in wireless video sensor network: definition and analysis , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.