Video transcoding for adaptive bitrate streaming over edge-cloud continuum

Video transcoding is to create multiple representations of a video for content adaptation.It is deemed as a core technique in Adaptive BitRate(ABR)streaming.How to manage video transcoding affects the performance of ABR streaming in various aspects,including operational cost,streaming delays,Quality of Experience(QoE),etc.Therefore,the problems of implementing video transcoding in ABR streaming must be systematically studied to improve the overall performance of the streaming services.These problems become more worthy of investigation with the emergence of the edge-cloud continuum,which makes the resource allocation for video transcoding more complicated.To this end,this paper provides an investigation of the main technical problems related to video transcoding in ABR streaming,including designing a rate profile for video transcoding,providing resources for video transcoding in clouds,and caching multi-bitrate video contents in networks,etc.We analyze these problems from the perspective of resource allocation in the edge-cloud continuum and cast them into resource and Quality of Service(QoS)optimization problems.The goal is to minimize resource consumption while guaranteeing the QoS for ABR streaming.We also discuss some promising research directions for the ABR streaming services.

A Content-Aware Bitrate Selection Method Using Multi-Step Prediction for 360-Degree Video Streaming

A content-aware multi-step prediction control(CAMPC)algorithm is proposed to determine the bitrate of 360-degree videos,aim⁃ing to enhance the quality of experience(QoE)of users and reduce the cost of video content providers(VCP).The CAMPC algorithm first em⁃ploys a neural network to generate the content richness and combines it with the current field of view(FOV)to accurately predict the probability distribution of tiles being viewed.Then,for the tiles in the predicted viewport which directly affect QoE,the CAMPC algorithm utilizes a multi-step prediction for future system states,and accordingly selects the bitrates of multiple subsequent steps,instead of an instantaneous state.Meanwhile,it controls the buffer occupancy to eliminate the impact of prediction errors.We implement CAMPC on players by building a 360-degree video streaming platform and evaluating other advanced adaptive bitrate(ABR)rules through the real network.Experimental results show that CAMPC can save 83.5%of bandwidth resources compared with the scheme that completely transmits the tiles outside the viewport with the Dynamic Adaptive Streaming over HTTP(DASH)protocol.Besides,the proposed method can improve the system utility by 62.7%and 27.6%compared with the DASH official and viewport-based rules,respectively.

Fuzzy Based Adaptive Deblocking Filters at Low-Bitrate HEVC Videos for Communication Networks

In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding(HEVC)frames and improves its subjective visual quality in multimedia services over communication networks.However,on faster processing of the complex videos at a low bitrate,some visible artifacts considerably degrade the picture quality.In this paper,we proposed a four-step fuzzy based adaptive deblocking filter selection technique.The proposed method removes the quantization noise,blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate.We have considered Y(luma),U(chromablue),and V(chroma-red)components parallelly.Finally,we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants,namely up 45◦,down 45◦,up 135◦,and down 135◦across horizontal and vertical block boundaries.In this context,experimentation is done on a wide variety of videos.An objective and subjective analysis is carried out with MATLAB software and Human Visual System(HVS).The proposed method substantially outperforms existing postprocessing deblocking techniques in terms of YPSNR and BD_rate.In the proposed method,we achieved 0.32–0.97 dB values of YPSNR.Our method achieved a BD_rate of+1.69%for the luma component,−0.18%(U)and−1.99%(V)for chroma components,respectively,with respect to the stateof-the-art methods.The proposed method proves to have low computational complexity and has better parallel processing,hence suitable for a real-time system in the near future.

An Improved NID Steganography Method for Low Bitrate Speech on VoIP

In the procedure of encoding process on low bitrate speech,fixed codebook division is an efficient and promising embedding method for steganography.An improved neighbor index division(NID)steganography method based on the high bitrate frame of G.723.1 codec(6.3kbit/s)is proposed,which employs the parity and low distortion of neighbor indices for G.723.1 fixed codebooks.Differing from previously NID method which performs quantized index modulation(QIM)beforehand,the proposed method divides codeword indices into separate sub-codebooks according to the secret message bits dynamically in the original G.723.1 codec quantization period.Compared with existing NID method,our proposed method doesn’t need to divide the codebook before the encoding starts.The embedding and codebook dividing happen simultaneously,which utilizes the characteristics of specific secret message bits.The experiment results show that the proposed method has a much lower quality degradation for the decoding speech and still fulfills the low latency requirement for communication.

Energy efficient fuzzy-based DASH adaptation algorithm

With the expansive demand for video streaming over mobile networks,it is necessary to adopt schemes that balance the need for high video quality with the available network resources when streaming or downloading the video.Several approaches were proposed in the literature,including Dynamic Adaptive Streaming over HTTP(DASH).In this work,we consider an approach in which we place sufficient emphasis on the constrained battery resources in mobile devices when making decisions on the quality(or bitrate)of the video to be requested.This is done by using a fuzzy logic controller that enhances the performance of the Fuzzy-based DASH(FDASH)scheme.Simulation results show that our proposed approach conserves more energy than its predecessor while maintaining similar video quality and avoiding playback interruptions.

新视点——SuperBit DVD

虽然世界九大公司刚刚联合发布了大容量蓝光DVD标准,新的标准有助于进一步提高图像分辨率,另外伴随着HDTV的虎视眈眈,仿佛更高清晰度的视频节目近在咫尺,但就现阶段而言,DVD仍然是主旋律.对于AV发烧友来说,只要有一丁点儿画质或音效的提高,也会乐此不疲,尤其是在选购DVD影片时更是如此.

QoE-Driven DASH Multicast Scheme for 5G Mobile Edge Network

Dynamic adaptive streaming over HTTP(DASH)can adaptively select the appropriate video bitrate for mobile users.Mobile edge computing(MEC)scenario is of great benefit to improve the performance of mobile networks by providing computing and storage capabilities.And the utilization of spectrum resources can be improved by multicast transmission,but the performance of the multicast transmission will be directly affected by the selected grouping algorithm and resource allocation algorithm.In order to improve the quality of experience(QoE)of video users in the 5G MEC scenario,this paper proposes a QoE-driven DASH multicast scheme,which mainly covers the grouping algorithm and the adaptive bitrate(ABR)algorithm.First of all,we take the optimized target QoE as the basis for grouping and propose an adaptive grouping algorithm that can dynamically adjust the grouping results.Besides,we design a joint optimization ABR algorithm based on the prediction of QoE,which comprehensively considers the process of resource allocation and bitrate decision-making based on the prediction of QoE of video segments in a certain forward-looking field of view.The simulation results show that the proposed DASH multicast scheme performs well in QoE and fairness.