Scalable transcoding for video transmission over space-time OFDM systems

A new scheme combining a scalable transcoder with space time block codes （STBC） for an orthogonal frequency division multiplexing （OFDM） system is proposed for robust video transmission in dispersive fading channels. The target application for such a scalable transcoder is to provide successful access to the pre-encoded high quality video MPEG-2 from mobile wireless terminals. In the scalable transcoder, besides outputting the MPEG-4 fine granular scalability （FGS） bitstream, both the size of video frames and the bit rate are reduced. And an array processing algorithm of layer interference suppression is used at the receiver which makes the system structure provide different levels of protection to different layers. Furthermore, by considering the important level of scalable bitstream, the different bitstreams can be given different level protection by the system structure and channel coding. With the proposed system, the concurrent large diversity gain characteristic of STBC and alleviation of the frequency-selective fading effect of OFDM can be achieved. The simulation results show that the proposed schemes integrating scalable transcoding can provide a basic quality of video transmission and outperform the conventional single layer transcoding transmitted under the random and bursty error channel conditions.

En-Route Transcoding缓存的优化放置和替换

对en-route transcoding缓存中的缓存路由和协同放置及替换问题进行了研究.提出了CCRA(cost-aware cache routing algorithm)缓存路由算法,能以可控的探测开销来发现潜在的、具有最小访问开销的缓存对象.在此基础上,建立了en-route transcoding缓存的分析模型,将缓存放置和替换问题形式化为一个最优化问题,并利用一种基于动态规划的方法来求解最佳缓存放置策略.仿真结果表明,与已有的元算法放置策略相比,该协同放置和替换策略可以获得更好的CSR性能.

MPEG-2到H.263 Transcoding的若干关键问题

该文在前人的工作基础上提出了在压缩域MPEG-2到H.263码流transcoding的通用框架,并进行了深入的分析和优化。这种优化的目标是,在实现视频流格式转换和瘦化的同时能够最大程度地利用源视频流的计算信息。该文对transcoding过程进行了形式化推导和分析,使transcoding的计算复杂性和存储消耗大大降低,同时理论上能实现在transcoding级上的更好视频质量(与传统方法相比)。这种通用框架能够以标准附件的形式加入高级应用功能,如数据隐藏模块、误码掩藏模块、链路适应模块。这种工作的意义在于,通过把transcoding复杂性推向网络边缘设备transcoder,降低了用户的硬件更新成本和视频服务器存储成本,使不同类型终端和不同链路环境的用户能够高效地透明地访问高质量视频流域。同时,计算复杂性和存储消耗的降低有利于服务器端以较低成本实现更多用户接入能力。

Energy-Efficient Joint Caching and Transcoding for HTTP Adaptive Streaming in 5G Networks with Mobile Edge Computing

With the new promising technique of mobile edge computing (MEC) emerging, by utilizing the edge computing and cloud computing capabilities to realize the HTTP adaptive video streaming transmission in MEC-based 5G networks has been widely studied. Although many works have been done, most of the existing works focus on the issues of network resource utilization or the quality of experience (QoE) promotion, while the energy efficiency is largely ignored. In this paper, different from previous works, in order to realize the energy efficiency for video transmission in MEC-enhanced 5G networks, we propose a joint caching and transcoding schedule strategy for HTTP adaptive video streaming transmission by taking the caching and transcoding into consideration. We formulate the problem of energy-efficient joint caching and transcoding as an integer programming problem to minimize the system energy consumption. Due to solving the optimization problem brings huge computation complexity, therefore, to make the optimization problem tractable, a heuristic algorithm based on simulated annealing algorithm is proposed to iteratively reach the global optimum solution with a lower complexity and higher accuracy. Finally, numerical simulation results are illustrated to demonstrated that our proposed scheme brings an excellent performance.

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.

MEC-Assisted Flexible Transcoding Strategy for Adaptive Bitrate Video Streaming in Small Cell Networks

Adaptive bitrate video streaming(ABR)has become a critical technique for mobile video streaming to cope with time-varying network conditions and different user preferences.However,there are still many problems in achieving high-quality ABR video streaming over cellular networks.Mobile Edge Computing(MEC)is a promising paradigm to overcome the above problems by providing video transcoding capability and caching the ABR video streaming within the radio access network(RAN).In this paper,we propose a flexible transcoding strategy to provide viewers with low-latency video streaming services in the MEC networks under the limited storage,computing,and spectrum resources.According to the information collected from users,the MEC server acts as a controlling component to adjust the transcoding strategy flexibly based on optimizing the video caching placement strategy.Specifically,we cache the proper bitrate version of the video segments at the edge servers and select the appropriate bitrate version of the video segments to perform transcoding under jointly considering access control,resource allocation,and user preferences.We formulate this problem as a nonconvex optimization and mixed combinatorial problem.Moreover,the simulation results indicate that our proposed algorithm can ensure a low-latency viewing experience for users.

Resynchronization and remultiplexing for transcoding to H.264/AVC

H.264/MPEG-4 AVC standard appears highly competitive due to its high efficiency, flexibility and error resilience. In order to maintain universal multimedia access, statistical multiplexing, or adaptive video content delivery, etc., it induces an immense demand for converting a large volume of existing multimedia content from other formats into the H.264/AVC format and vice versa. In this work, we study the remultiplexing and resynchronization issue within system coding after transcoding, aiming to sustain the management and time information destroyed in transcoding and enable synchronized decoding of decoder buffers over a wide range of retrieval or receipt conditions. Given the common intention of multiplexing and synchronization mechanism in system coding of different standards, this paper takes the most widely used MPEG-2 transport stream (TS) as an example, and presents a software system and the key technologies to solve the time stamp mapping and relevant buffer management. The solution reuses previous information contained in the input streams to remultiplex and resynchronize the output information with the regulatory coding and composition structure. Experimental results showed that our solutions efficiently preserve the performance in multimedia presentation.

Fast mode decision algorithm for spatial resolutions down-scaling transcoding to H.264

A fast mode decision algorithm is proposed in this paper to accelerate the process of transcoding videos into H.264with arbitrary rate spatial resolution down-scaling. The proposed algorithm consists of three steps. First, an early-stop technique is introduced to determine the 16× 16-mode blocks, which take up about 70% of all the macroblocks; then, a bottom-up merging process is performed to determine the mode of rest non-early-stopped blocks; and then, we adopt half-pixel motion estimation to further refine the acquired predictive motion vectors. In order to obtain the predictive motion vectors for early-stop and merging processes, we propose a motion vector composition scheme, which can reuse the information in the input pre-encoded videos to handle the spatial resolution down-scaling. Experimental results showed that our algorithm is about four times faster than the Cascaded-Decoder-Encoder method and has negligible PSNR drop and little bit rate increase.

Fast Intra Downsizing Based on Direction for H.264/AVC Transcoding

A fast algorithm based on direction in intra frame downsizing in H.264 is proposed,which used modes information of macroblocks before transcoding and the direction relation of modes between decoding and re-encoding in transcoding.This algorithm also made use of statistics between decoded modes and re-encoded modes,which came from a lot of sequences data experiments.Without full modes encoding,it can improve the speed of reducing intra-prediction frame resolution obviously.Comparing to traditional transcoding,it only needs to compute one of thirteen modes in re-encoding.The experiments show that this algorithm can significantly speed up 92 percent transcoding time in intra-prediction frame of H.264 with slight PSNR degradation.It also can support an improvement in real-time for transcoding and ability of bandwidths changing.

Scheduling Heuristics for Live Video Transcoding on Cloud Edges

Efficient video delivery involves the transcoding of the original sequence into various resolutions,bitrates and standards,in order to match viewers’capabilities.Since video coding and transcoding are computationally demanding,performing a portion of these tasks at the network edges promises to decrease both the workload and network traffic towards the data centers of media providers.Motivated by the increasing popularity of live casting on social media platforms,in this paper we focus on the case of live video transcoding.Specifically,we investigate scheduling heuristics that decide on which jobs should be assigned to an edge minidatacenter and which to a backend datacenter.Through simulation experiments with different Qo S requirements we conclude on the best alternative.

Mode decision for H.264 down-scaling video transcoding

Although the coding modes of H.264 coded video would be changed by the transcoding process of spatial resolution reduction, there exists good correlation in prediction modes and prediction directions between input and output video. In this paper, we first introduce a new spatial resolution reduction transcoding architecture of intra coded frames where the distortion can be calculated directly in compression domain. We then propose a fast mode decision algorithm in which only a small part of rate distortion optimization （RDO） calculation is needed for mode decision. For 4×4 luma block, the proposed scheme has average 21.3% computation saving, compared to the cascaded pixel-domain transcoding scheme with the fast intra mode decision algorithm proposed in JVT-G013. For 16×16 luma block, RDO calculation is completely avoided in our scheme while the scheme in JVT-G013 needs 2 RDO calculations. Experimental results show that our scheme outperforms that of JVT-G013 in terms of significantly computasavings with negligible loss of PSNR

ZTE IPTV Low Bit Rate High Definition Transcoding Solution Nominated for Global IPTV Industry Award

ZTE Corporation announced on 1 March that its innovative IPTVlowbitrate highdefinition transcoding solution has been nominated for the World＇s Best Component or Enabler Award by the IPTV World Forum. The ZTE solution is on display at the Mobile World Congress 2012 （MWC 2012） in Barcelona.

Visible Watermarking Technique for MPEG-2 Downsampling Transcoding in the DCT Domain

To locate the right places for embedding watermark signals, and to set the proper streng-th of the embedded watermark signal are two critical problems for obtaining a robust and transpar-ent watermark in color images. In this paper, a DCT domain visible watermarking scheme based on the luminance and texture features and alligned with transcoding from MPEG-2 to MPEG-1 is proposed. In this scheme, the location of the visible watermark is chosen at the block with minimum number of nonzero DCT coefficients in the I-frames. When embedding the visible watermark （ such as video DC image ） into the unmarked original image, the embedding factors are determined with the local luminance feature and texture features of the original image and watemark image by utilizing DC and 3AC coefficients only. Experimental results demonstrate that the proposed scheme not only provides good fidelity and robustness against MPEG-2 downscaling transcoding, but also achieves a low Computational complexity.

FSpot:Fast and Efficient Video Encoding Workloads Over Amazon Spot Instances

HTTP Adaptive Streaming(HAS)of video content is becoming an undivided part of the Internet and accounts for most of today’s network traffic.Video compression technology plays a vital role in efficiently utilizing network channels,but encoding videos into multiple representations with selected encoding parameters is a significant challenge.However,video encoding is a computationally intensive and time-consuming operation that requires high-performance resources provided by on-premise infrastructures or public clouds.In turn,the public clouds,such as Amazon elastic compute cloud(EC2),provide hundreds of computing instances optimized for different purposes and clients’budgets.Thus,there is a need for algorithms and methods for optimized computing instance selection for specific tasks such as video encoding and transcoding operations.Additionally,the encoding speed directly depends on the selected encoding parameters and the complexity characteristics of video content.In this paper,we first benchmarked the video encoding performance of Amazon EC2 spot instances using multiple×264 codec encoding parameters and video sequences of varying complexity.Then,we proposed a novel fast approach to optimize Amazon EC2 spot instances and minimize video encoding costs.Furthermore,we evaluated how the optimized selection of EC2 spot instances can affect the encoding cost.The results show that our approach,on average,can reduce the encoding costs by at least 15.8%and up to 47.8%when compared to a random selection of EC2 spot instances.

Intelligent Mobile Video Surveillance System with Multilevel Distillation

This paper proposes a mobile video surveillance system consisting of intelligent video analysis and mobile communication networking. This multilevel distillation approach helps mobile users monitor tremendous surveillance videos on demand through video streaming over mobile communication networks. The intelligent video analysis includes moving object detection/tracking and key frame selection which can browse useful video clips. The communication networking services, comprising video transcoding, multimedia messaging, and mobile video streaming, transmit surveillance information into mobile appliances. Moving object detection is achieved by background subtraction and particle filter tracking. Key frame selection, which aims to deliver an alarm to a mobile client using multimedia messaging service accompanied with an extracted clear frame, is reached by devising a weighted importance criterion considering object clarity and face appearance. Besides, a spatial- domain cascaded transcoder is developed to convert the filtered image sequence of detected objects into the mobile video streaming format. Experimental results show that the system can successfully detect all events of moving objects for a complex surveillance scene, choose very appropriate key frames for users, and transcode the images with a high power signal-to-noise ratio （PSNR）.

Efficient video downscaling transcoder from MPEG-2 to H.264

The new H.264 video coding standard achieves significantly higher compression performance than MPEG-2. As the MPEG-2 is popular in digital TV, DVD, etc., bandwidth or memory space can be saved by transcoding those streams into H.264 in these applications. Unfortunately, the huge complexity keeps transcoding from being widely used in practical applications. This paper proposes an efficient transcoding architecture with a smart downscaling decoder and a fast mode decision algorithm. Using the proposed architecture, huge buffering memory space is saved and the transcoding complexity is reduced. Performance of the proposed fast mode decision algorithm is validated by experiments.

mRNA Dependent Virtual-Real Substitutions of Nucleotides in Codons: The Dynamics of Their Meanings in the Genome Language

This is an attempt to explain mRNA-dependent non-stationary semantic values of codons (triplets) and nucleotides (letters) in codon composition during protein biosynthesis. This explanation is realized by comparing the different protein codes of various biosystem taxa, and, comparing mitochondrial code with the standard code. An initial mRNA transcriptional virtuality (Virtual-Reality) is transformed into material reality at the level of translation of virtual triplets into real (material) amino acids or into a real stop command of protein biosynthesis. The transformation of virtuality into reality occurs de facto when the linguistic sign1 functions of the codon syhoms are realized in the 3’ nucleotide (wobbling nucleotide according to F. Crick) in the process of protein biosynthesis. This corresponds to the theoretical works of the authors of this article. Despite the illusory appearance of semantic arbitrariness during the operation of ribosomes in the mode of codon semantic non-stationarity, this phenomenon probably provides biosystems with an unusually high level of adaptability to changes in the external environment as well as to internal (mental) dynamics of neuron’s genome in the cerebral cortex. The genome’s non-stationarity properties at the nucleotide, codon, gene and mental levels have fractal structure and corresponding dimensions. The highest form of such fractality (with maximum dimension) is probably realized in the genomic continuum of neurons in the human cerebral cortex through this semantic Virtual-to-Real (VR) codon transcoding with the biosynthesis of short-living semantic proteins, as the equivalents of material thinking-consciousness. In fact, this is the language of the brain’s genome, that is, our own language. In this case, the same thing happens in natural, primarily mental (non-verbal) languages. Their materialization is recorded in vocables (sounding words) and in writing. Such writing is the amino acid sequence in the semantic proteins of the human cerebral cortex. Rapidly decaying, such proteins can leave a long-lasting “so-called” Schrödinger wave holographic memory in the cerebral cortex. The presented below study is purely theoretical and based on a logical approach. The topic of the study is very complex and is subject to further development.

诺基亚2I BSC利旧的探讨

诺基亚2I的BSCTC与3I的TC单板类型相似,所以考虑可以通过改造将报废2IBSC的TC利用到现网。由于春节期间齐齐哈尔BSC部分A口话务负荷较高,但3IBSC设备已经无硬件可扩容,考虑到2I设备已报废,有闲置的TC硬件可以利旧。齐齐哈尔经过反复调测与实验,将2I设备TC利旧成功。

Adaptive rate control on wireless transcoder

To guarantee the real-time transmission of a video stream, based on the stochastic optimal control method, a frame layer adaptive rate control algorithm for the wireless transcoder is proposed, which is capable of dynamically determining the transcoder＇s objective bit rate, according to the bandwidth variation of the wireless channel and the buffer occupancy. Then the transient performance, steady performance, and computational complexity of the algorithm are analyzed. Finally, the experiment results demonstrate that the algorithm can improve the synthetic performance of rate control through the compromise between the end-to-end delay and the playout quality.

TransCode:Uncovering COVID-19 transmission patterns via deep learning

Background The heterogeneity of COVID-19 spread dynamics is determined by complex spatiotemporal transmission patterns at a fine scale,especially in densely populated regions.In this study,we aim to discover such fine-scale transmission patterns via deep learning.Methods We introduce the notion of TransCode to characterize fine-scale spatiotemporal transmission patterns of COVID-19 caused by metapopulation mobility and contact behaviors.First,in Hong Kong,China,we construct the mobility trajectories of confirmed cases using their visiting records.Then we estimate the transmissibility of individual cases in different locations based on their temporal infectiousness distribution.Integrating the spatial and temporal information,we represent the TransCode via spatiotemporal transmission networks.Further,we propose a deep transfer learning model to adapt the TransCode of Hong Kong,China to achieve fine-scale transmission characterization and risk prediction in six densely populated metropolises:New York City,San Francisco,Toronto,London,Berlin,and Tokyo,where fine-scale data are limited.All the data used in this study are publicly available.Results The TransCode of Hong Kong,China derived from the spatial transmission information and temporal infectiousness distribution of individual cases reveals the transmission patterns(e.g.,the imported and exported transmission intensities)at the district and constituency levels during different COVID-19 outbreaks waves.By adapting the TransCode of Hong Kong,China to other data-limited densely populated metropolises,the proposed method outperforms other representative methods by more than 10%in terms of the prediction accuracy of the disease dynamics(i.e.,the trend of case numbers),and the fine-scale spatiotemporal transmission patterns in these metropolises could also be well captured due to some shared intrinsically common patterns of human mobility and contact behaviors at the metapopulation level.Conclusions The fine-scale transmission patterns due to the metapopulation level mobility(e.g.,travel across different districts)and contact behaviors(e.g.,gathering in social-economic centers)are one of the main contributors to the rapid spread of the virus.Characterization of the fine-scale transmission patterns using the TransCode will facilitate the development of tailor-made intervention strategies to effectively contain disease transmission in the targeted regions.