New Rate Allocation Method for MPEG-4 FGS Video Streaming

A new rate allocation method for fine-granular scalability (FGS) coded bitstreams is presented in order to achieve smooth quality reconstruction of frames under channel conditions with a wide range of bandwidth variation and improve the average PSNR of the whole sequence. Based on a quality weighted bit allocation method, a sliding window rate allocation method is proposed for the first time so that the window can slide along the video sequence with a certain sliding step. Experimental results show that, under dynamic bandwidth conditions, the proposed method can simultaneously satisfy the requirements for improving average PSNR of the whole video sequence greatly and reducing the fluctuations between adjacent frames greatly.

Optimal Rate Allocation Algorithm for Multiple Source Video Streaming

Video streaming is one of the most important applications used in the best-effort Internet. This paper presents a new scheme for multiple source video streaming in which the traditional fine granular scal-able coding was rebuilt into a multiple sub-streams based transmission model. A peak signal to noise ratio based stream rate allocation algorithm was then developed based on the transmission model. In tests, the algorithm performance is about 1 dB higher than that of a uniform rate allocation algorithm. Therefore, this scheme can overcome bottlenecks along a single link and smooth jitter to achieve high quality and stable video.

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.

A probabilistic approach for predictive congestion control in wireless sensor networks

Any node in a wireless sensor network is a resource constrained device in terms of memory, bandwidth, and energy, which leads to a large number of packet drops, low throughput, and significant waste of energy due to retransmission. This paper presents a new approach for predicting congestion using a probabilistic method and controlling congestion using new rate control methods. The probabilistic approach used for prediction of the occurrence of congestion in a node is developed using data traffic and buffer occupancy. The rate control method uses a back-off selection scheme and also rate allocation schemes, namely rate regulation(RRG) and split protocol(SP), to improve throughput and reduce packet drop. A back-off interval selection scheme is introduced in combination with rate reduction(RR) and RRG. The back-off interval selection scheme considers channel state and collision-free transmission to prevent congestion. Simulations were conducted and the results were compared with those of decentralized predictive congestion control(DPCC) and adaptive duty-cycle based congestion control(ADCC). The results showed that the proposed method reduces congestion and improves performance.