Optimal Content Placement and Request Dispatching for Cloud-based Video Distribution Services

The rapid progress of cloud technology has attracted a growing number of video providers to consider deploying their streaming services onto cloud platform for more cost-effective, scalable and reliable performance. In this paper, we utilize Markov decision process model to formulate the dynamic deployment of cloud-based video services over multiple geographically distributed datacenters. We focus on maximizing the average profits for the video service provider over a long run and introduce an average performance criteria which reflects the cost and user experience jointly. We develop an optimal algorithm based on the sensitivity analysis and sample-based policy iteration to obtain the optimal video placement and request dispatching strategy. We demonstrate the optimality of our algorithm with theoretical proof and specify the practical feasibility of our algorithm. We conduct simulations to evaluate the performance of our algorithm and the results show that our strategy can effectively cut down the total cost and guarantee users＇ quality of experience （QoE）.

A WYNER-ZIV VIDEO CODING METHOD UTILIZING MIXTURE CORRELATION NOISE MODEL

In Wyner-Ziv (WZ) Distributed Video Coding (DVC), correlation noise model is often used to describe the error distribution between WZ frame and the side information. The accuracy of the model can influence the performance of the video coder directly. A mixture correlation noise model in Discrete Cosine Transform (DCT) domain for WZ video coding is established in this paper. Different correlation noise estimation method is used for direct current and alternating current coefficients. Parameter estimation method based on expectation maximization algorithm is used to estimate the Laplace distribution center of direct current frequency band and Mixture Laplace-Uniform Distribution Model (MLUDM) is established for alternating current coefficients. Experimental results suggest that the proposed mixture correlation noise model can describe the heavy tail and sudden change of the noise accurately at high rate and make significant improvement on the coding efficiency compared with the noise model presented by DIStributed COding for Video sERvices (DISCOVER).

A Distributed 2D-to-3D Video Conversion System

2D-to-3D video conversion is a feasible way to generate 3D programs for the current 3DTV industry. However, for large-scale 3D video production, current systems are no longer adequate in terms of the time and labor required for conversion. In this paper, we introduce a distributed 2D-to-3D video conversion system that includes a 2D-to-3D video conversion module, architecture of the parallel computation on the cloud, and 3D video coding in the system. The system enables cooperation among multiple users in the simultaneous completion of their conversion tasks so that the conversion efficiency is greatly promoted. In the experiments, we evaluate the system based on criteria related to both time consumption and video coding performance.

Distributed Adaptive Compressed Video Sensing Using Smoothed Projected Landweber Reconstruction

A novel Compressed-Sensing-based(CS-based)Distributed Video Coding(DVC)system,called Distributed Adaptive Compressed Video Sensing(DISACOS),is proposed in this paper.In this system,the input frames are divided into key frames and non-key frames,which are encoded by block CS sampling.The key frames are encoded as CS measurements at substantially higher rates than the non-key frames and decoded by the Smoothed Projected Landweber(SPL)algorithm using multi-hypothesis predictions.For the non-key frames,a small number of CS measurements are first transmitted to detect blocks having low-quality Side Information(SI)generated by the conventional interpolation or extrapolation at the decoder;then,another group of CS measurements are sampled again upon the decoder’s request.To fully utilise the CS measurements,we adaptively allocate these measurements to each block in terms of different edge features.Finally,the residual frame is reconstructed using the SPL algorithm and the decoded non-key frame is simply determined as the sum of the residual frame and the SI.Experimental results have revealed that our CS-based DVC system yields better rate-distortion performance when compared with other schemes.

Trifocal tensor based side information generation for multi-view distributed video code

Distributed video coding （DVC） is a new video coding approach based on Wyner-Ziv theorem. The novel uplink-friendly DVC, which offers low-complexity, low-power consuming, and low-cost video encoding, has aroused more and more research interests. In this paper a new method based on multiple view geometry is presented for spatial side information generation of uncalibrated video sensor network. Trifocal tensor encapsulates all the geometric relations among three views that are independent of scene structure; it can be computed from image correspondences alone without requiring knowledge of the motion or calibration. Simulation results show that trifocal tensor-based spatial side information improves the rate-distortion performance over motion compensation based interpolation side information by a maximum gap of around 2dB. Then fusion merges the different side information （temporal and spatial） in order to improve the quality of the final one. Simulation results show that the rate-distortion gains about 0.4 dB.

A NEW APPROACH TO DVC COMBINED WITH ROI EXTRACTION AND RESIDUAL VIDEO CODING FOR MULTIMEDIA SENSOR NETWORKS

The Wyner-Ziv distributed video coding scheme is characterized for its intraframe encoder and interframe decoder which can also approach the efficiency of an interframe encoder-decoder system. In Wyner-Ziv residual coding of video, the residual of a frame with respect to a reference frame is Wyner-Ziv encoded, which can reduces the input entropy and leads to a higher coding efficiency than directly encoding the original frame. In this paper, we propose a new approach of residual coding combined with Region Of Interest (ROI) extraction. Experimental results show that, the proposed scheme achieves better rate-distortion performance compared to conventional Wyner-Ziv coding scheme.

Side information refinement in distributed video coding

Side information （SI） is one of the key issues in distributed video coding （DVC） and affects the compression performance of DVC largely. This paper proposes an SI refinement algorithm, in which the Wyner-Ziv （WZ） frame is split into two parts based on checkerboard pattern, and the two parts are encoded independently but decoded sequentially. In the decoding process, the part 1 is first decoded with the initial SI and partially decoded part （PDP） 1 is used to improve the motion vectors （MVs） and SI of both parts. At the next stage, the part 2 is decoded with the improved SI and PDP 2 is used to further refine MVs of the part 2. Then, SI of both parts are further refined. Simulation results show that the proposed algorithm can improve the peak signal to noise ratio （PSNR） by up to 1.43 dB when compared with traditional DVC codec.

MAP based blocking artifact reduction for DCT domain distributed video coding

This paper proposes a maximum a posteriori （MAP） based blocking artifact reduction algorithm for discrete cosine transform （DCT） domain distributed video coding, in which the SI and the initial reconstructed Wyner-Ziv （WZ） frame are utilized to further estimate the original WZ frame. Though the MAP estimate improves quality of the artifact region, it also leads to over-smoothness and decreases quality of the non-artifact region. To overcome this problem, a criterion is presented to discriminate the artifact and the non-artifact region in the initial reconstructed WZ frame, and only the artifact region is updated with the MAP estimate. Simulation results show that the proposed algorithm provides obvious improvement in terms of both objective and subjective evaluations.

Dynamic Global-Principal Component Analysis Sparse Representation for Distributed Compressive Video Sampling

Video reconstruction quality largely depends on the ability of employed sparse domain to adequately represent the underlying video in Distributed Compressed Video Sensing (DCVS). In this paper, we propose a novel dynamic global-Principal Component Analysis (PCA) sparse representation algorithm for video based on the sparse-land model and nonlocal similarity. First, grouping by matching is realized at the decoder from key frames that are previously recovered. Second, we apply PCA to each group (sub-dataset) to compute the principle components from which the sub-dictionary is constructed. Finally, the non-key frames are reconstructed from random measurement data using a Compressed Sensing (CS) reconstruction algorithm with sparse regularization. Experimental results show that our algorithm has a better performance compared with the DCT and K-SVD dictionaries.

Design of the Quantization Matrix in the Distributed Compressed Sensing Video Coding*

In the frame of compressed sensing distributed video coding, the design of the quantization matrix directly affects the reconstruction quality of the receiving terminal of the video. In this article, we present a new design method of the Gaussian quantization matrix adapting to the compressed sensing coding, for that the distribution of the parameters of the image is featured of the characteristic of approximately normal distribution after measured by compressive sensing. By this way, the parameters of a certain quantity of the image frames depending on the video sequences generated by the Gaussian quantization matrix possess certain adaptive capacity. By comparison with the plan of the traditional quantization, the quantization matrix presented in this article would improve the reconstruction quality of the video.

Application of Bit Error Rate Information Based on Weighted Error Estimating Code

Error Estimating Code (EEC) is a new channel coding method to estimate the Bit Error Rate (BER) information of the transmitted sequence. However, the estimated BER is not precise enough if the practical value of BER is high. A weighted EEC estimation method is proposed to improve the accuracy performance of BER estimation by classifying the raw estimation results into intervals and multiplying them by different coefficients separately. The applications of weighted EEC in modulation selection scheme and distributed video coding are discussed. Simulation results show that the EEC-based modulation selection method can achieve better performance at a cost of little redundancy and computation, and the EEC-based rate estimation method in distributed video coding can save the decoding time.

Rate estimate for regular LDPCA codec in distributed video coding

Accumulated low density parity check （LDPCA） codec is proposed for DISCOVER project in distributed video coding （DVC）, which offers flexible coding rate. Although it can use feedback channel to adapt the rate to the correlation of the video, but in real applications, using feedback channel can not always be possible. To solve this problem, some researchers proposed estimating the code rate at the encoder but the performance was not very good. Based on their researches, this paper considers the impact of convergence rate for iteration on rate estimate, which can be calculated using its check matrix. As a pilot study, this paper pays attention to the regular LDPCA codec. At the same time, it considers the impact of deviation in the estimated crossover probability, which gives some constraints to rate estimate. In the experiment, the proposed algorithm can improve the rate-distortion performance by up to 1 dB-1.2 dB.

Robust multiple description distributed video coding using optimized zero-padding

Distributed video coding （DVC） arouses high interests due to its property of low-complexity encoding. This paper proposes a robust multiple description DVC （MDDVC） under the constraint of low-complexity encoding. In MDDVC, zeros are padded to each frame and the resulting big-size video is divided into multiple descriptions. Then, each description is compressed by s hybrid DVC （HDVC） codec and trans- mitted over different channel. When one channel does not work, the lost HDVC description is estimated by the received from other channel, which guarantees the robustness of the system; MDDVC moves the complex motion estimation totally to the decoder so it features low-complexity encoding. In the pre-processing, an optimized zero-padding is also proposed to improve the performance. Experimental results exhibit that the proposed MDDVC scheme achieves better rate-distortion performance and robustness than the referenced especially when packet-loss rate is high.

Efficient reconstruction scheme for transform domain Wyner-Ziv video coding

To minimize the errors of the reconstructed values and improve the quality of decoded image, an efficient reconstruction scheme for transform domain Wyner-Ziv （WZ） video coding is proposed. The reconstruction scheme exploits temporal correlation of the coefficient bands, the WZ decoded bits stream and the side information efficiently. When side information is outside the decoded quantization bin, the reconstructed value is derived using expectation of the WZ decoded bit stream and the side information. When side information is within the decoded quantization bin, the reconstructed value is derived using the biased predictor. Simulation results show that the proposed reconstruction scheme gains up to 1.32 dB compared with the commonly used boundary reconstruction scheme at the same bit rates and similar computation cost.

Distributed video coding with adaptive selection of hash functions

We address the compression efficiency of feedback-free and hash-check distributed video coding,which generates and transmits a hash code of a source information sequence.The hash code helps the decoder perform a motion search.A hash collision is a special case in which the hash codes of wrongly reconstructed information sequences occasionally match the hash code of the source information sequence.This deteriorates the quality of the decoded image greatly.In this paper,the statistics of hash collision are analyzed to help the codec select the optimal trade-off between the probability of hash collision and the length of the hash code,according to the principle of rate-distortion optimization.Furthermore,two novel algorithms are proposed:(1) the nonzero prefix of coefficients (NPC),which indicates the count of nonzero coefficients of each block for the second algorithm,and also saves 8.4% bitrate independently;(2) the adaptive selection of hash functions (AHF),which is based on the NPC and saves a further 2%-6% bitrate on average.The detailed optimization of the parameters of AHF is also presented.

Hash signature saving in distributed video coding

In transform-domain distributed video coding (DVC), the correlation noises (denoted as N) between the source block and its temporal predictor can be modeled as Laplacian random variables. In this paper we propose that the noises (denoted as N′) between the source block and its co-located block in a reference frame can also be modeled as Laplacian random variables. Furthermore, it is possible to exploit the relationship between N and N′ to improve the performance of the DVC system. A practical scheme based on theoretical insights, the hash signature saving scheme, is proposed. Experimental results show that the proposed scheme saves on average 83.2% of hash signatures, 13.3% of bit-rate, and 3.9% of encoding time.

A new encoder rate-allocation method for distributed video coding

Distributed video coding(DVC)is a new video coding architecture.Compared with traditional video coding schemes,DVC has a simple encoder and complex decoder,which makes it suitable for circumstances where the encoder equipments are simple but the decoder equipments are complex.Most of the existing DVC architectures use decoder rate allocation method with the help of feedback channel.According to the results of the current decoding round,the decoder informs the encoder by feedback channel whether more parity bits are needed.The use of feedback channel not only increases the system delay,but also limits the use of DVC to instances where there is no feedback channel.In this paper,we propose a novel encoder rate allocation method.First,the simple three-step motion estimation is introduced into the encoder to estimate the side information of the decoder,and then the number of parity bits the decoder needs for each bitplane is allocated at the encoder according to the difference of the estimated side information and the current Wyner-Ziv(WZ)frame.Experiment results indicate that the accuracy of the proposed method is 5.18%-52.93% higher than that of the method proposed by Morbee.