In this paper, we consider roadside infrastructure-to-roadside infrastructure communications in a vehicular ad hoc network. A remote roadside unit (RSU), which does not have connection to the backbone network, needs to send its data traffic to a central RSU (which has backbone connection) by using help from vehicles passing by. Cost is assigned to information transmission energy consumption, as well as possible violation of a soft delay bound. For each passing vehicle, the remote RSU needs to decide whether or not to ask for help from the vehicle, with a target at a minimal rate of cost. We derive an optimal decision strategy of the remote RSU, which is shown to have a conditional pure-threshold structure, i.e., when a vehicle arrives at the remote RSU, if the queuing delay of the data traffic at the remote RSU is above a threshold, it is optimal for the remote RSU to ask for help from the vehicle, with a condition that the vehicle's speed satisfies a requirement. We also provide a method that can theoretically derive the threshold. The conditional pure-threshold structure makes our derived strategy very easy to implement with very low computation complexity.

In this paper, a novel cross-layer optimization scheme for video streaming in wireless relay networks is proposed. It takes into account of delay constraints at the application (APP) layer, relay node selection at the MAC layer and dynamic fading of wireless channels at the physical (PHY) layer in an integrated mode to improve the quality of video transmission. At the PHY layer, a finite state Markov channels (FSMC) model is used to estimate the channel states and a modified RTS/CTS scheme is proposed to facilitate the path selection at the MAC layer. The impacts of delay constraints and other factors at the APP layer are investigated. At the MAC layer, the source node can choose the proper path to transmit video data while considering video delay requirements and wireless channel states simultaneously. A typical three-node uploading scenario in video surveillance applications is considered as an example for performance evaluation. The experimental results show that the proposed scheme could improve video transmission quality and achieve a near-optimal performance.

A transrating-assisted spatial resolution conversion method for compressed videos is proposed. By utilizing the property of equivalence between downsampling of the video spatial resolution and bitrate reducing of the video streams in frequency domain, it implements video resizing through transrating. That is, it decodes the compressed video stream and then reencodes it to a new bitrate corresponding to the target video spatial resolution instead of direct changing the video spatial resolution before the conversion like the traditional spatial transcoding, which facilitates efficient using of motion vectors and macroblock modes. To alleviate mismatching between the original bitrate allocation mechanism and the newly-changed distribution of the discrete cosine transform(DCT) coefficients, a tactic which only proactively sets the high frequency DCT coefficients of P frames to zeros is used in the transrating process to implicitly implement subsampling of the video. Experimental results show that it can significantly improve the rate-distortion performance of the obtained video streams.

This paper proposes a novel approach to predict the video decoding computational complexity. The decoding complexity of each frame is found having an approximate linear relationship with the frame length, whereas the motion Information (MI) and the amount of encoded residual coefficients (ERC) are proved to be the two main factors that affect the variation of the model parameters. The changing rule of MI and ERC for different kinds of video contents are investigated, which in turn derives the variation regularity of the model parameters. Then the correlation between the model parameters of neighboring frames is defined as a piecewise function under the constraint of video motion complexity. The derived piecewise function is used to predict the decoding complexity online, and the prediction error is utilized as the feedback to update the model parameters adaptively. Experimental results show that the proposed method can give fairly accurate prediction for the decoding complexity with very low overhead. The average prediction errors for various test sequences are all within 7%.

This paper presents a new scheme for robust video transmission over packet erasure wireless channels based on Wyner-Ziv coding of motion regions. The multipath fading and shading of the wireless channels usually lead to loss or erroneous video packets which on occasions result in some spontaneous drop in video quality. Existing approaches with forward error correction (FEC) and error concealment have not been able to provide the desired robustness in video transmission. We develop a new scheme with a motion-based Wyner-Ziv coding (MWZC) by leveraging distributed source coding (DSC) ideas for error robustness. This new scheme is based on the fact that motion regions of a given video frame are particularly important in both objective and perceptual video quality and hence should be given preferential Wyner-Ziv coding based embedded protection. To achieve high coding efficiency, we determine the underlining motion regions based on a rate-distortion model. Within the framework of H.264/AVC specification, motion region determination can be efficiently implemented using flexible macroblock ordering (FMO) and data partitioning (DP). The bit stream generated by the proposed scheme consists two parts: the systematic portion generated from conventional H.264/AVC bit stream and the supplementary bit stream for error robust video transmission generated by the Wyner-Ziv coding of motion regions. Experimental results demonstrate that the proposed scheme significantly outperforms both decoder-based error concealment (DBEC) and conventional FEC with DBEC approaches.

In this paper, we propose a new rate allocation algorithm for transform domain Wyner-Ziv video coding (WZVC) without feedback. In contrast to conventional video coding, Wyner-Ziv video coding aims to design simple intra-frame encoding and complex inter-frame decoding based on the Slepian-Wolf and Wyner-Ziv distributed source coding theorems. To allocate proper number of bits to each frame, most existing Wyner-Ziv video coding solutions need a feedback channel (FC) at the decoder. However, in many video coding applications, the FC is not allowed. Moreover, the FC will introduce latency and an increase of decoder complexity because several iterative decoding operations may be needed to decode the data to achieve target video quality. The proposed algorithm predicts the number of bits for each Wyner-Ziv frame at the encoder as a function of the coding mode and the quantization parameters. Such predictions will not significantly increase the complexity at the encoder. However, the prediction will be able to properly select the best mode and quantization parameter for encoding each Wyner-Ziv frame. Experimental results show that the proposed algorithms is able to achieve good encoder rate allocation while still maintains consistent coding efficiency. Comparing to the WZVC coder with FC, this new WZVC coder without FC induces only a small loss in Rate-Distortion performance.