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检索条件"主题词=Transcoding"

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Cost optimal video transcoding in media cloud: Insights from user viewing pattern

Cost optimal video transcoding in media cloud: Insights from...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Guanyu Gao Weiwen Zhang Yonggang Wen Zhi Wang Wenwu Zhu Yap Peng Tan Nanyang Technological University Singapore Graduate School at Shenzhen Tsinghua University China Tsinghua University China

ISBN: (纸本)9781479947607

Video transcoding has been touted as an enabling technology to support growing media consumption over heterogenous devices. However, on-line transcoding could incur tremendous, if not prohibitive, cost in deploying or renting resources. In this research, we leverage an insight into the viewing pattern of video consumers to reduce the operating cost of video transcoding services. Specifically, it has been reported that viewers tend to terminate their session before the whole video is watched. As such, it is not cost-efficient for service providers to store or transcode all segments of the videos. Built upon this insight, we propose a partial transcoding scheme for content management in a media cloud to reduce the operating cost. Particularly, each content is split into multiple segments and stored in different files of varying playback rates. Some of the segments are stored in cache, resulting in storage cost; while some are transcoded in real-time in case of cache miss, resulting in computing cost. We aim to minimize the long-term operational cost by determining the number of segments for each playback rate to be cached or transcoded in real-time. We formulate this partial transcoding scheme as a constrained integer optimization problem. Leveraging Lagrangian relaxation and a subgradient method, we obtain the approximate solution to the integer program. Numerical results indicate that our proposed partial transcoding scheme can save more than 30% of operational cost, compared with a brute-force scheme of caching all the segments.

关键词： transcoding Streaming media Media Engines Content management Optimization Real-time systems

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Joint Online transcoding and Geo-distributed Delivery for Dynamic Adaptive Streaming

Joint Online Transcoding and Geo-distributed Delivery for Dy...

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IEEE International Conference on Computer Communications

作者： Zhi Wang Lifeng Sun Chuan Wu Wenwu Zhu Shiqiang Yang Department of Computer Science and Technology Tsinghua University Department of Computer Science The University of Hong Kong

Dynamic adaptive video streaming has emerged as a popular approach for video streaming in today's Internet. To date the two important components in dynamic adaptive streaming, video transcoding which generates the adaptive bitrates of a video and video delivery which streams the videos to users, have been separately studied, resulting in a huge waste of computation and storage resource due to transcoding useless videos and suboptimal streaming quality due to homogeneous video replication. In this paper, we propose to jointly perform video transcoding and video delivery for adaptive streaming in an online manner. We conduct extensive measurement studies of a video sharing system and a CDN to motivate our design. We formulate and solve optimization problems to enable high streaming quality for the users, and low computation and replication costs for the system. In particular, our design connects video transcoding and video delivery based on users' preferences of CDN regions and regional preferences of video versions. Extensive trace-driven experiments further confirm the superiority of our design.

关键词： Servers Streaming media transcoding Bandwidth Bit rate Joints Availability

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An encryption algorithm of JPEG2000 streams for supporting ciphertext-based transcoding

An encryption algorithm of JPEG2000 streams for supporting c...

引用

International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

作者： Yong Fu Xiaowei Yi Hengtai Ma Sci. and Tech. on Integrated Information System Lab. Chinese Academy of Sciences Beijing China State Key Laboratory of Information Security Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781479967339

With the increasing demands on image transcoding in heterogeneous networks, a ciphertext-based transcoding hierarchical encryption algorithm (CT-HEA) is proposed for JPEG2000 streams. By utilizing the rate-distortion optimized truncation, CT-HEA rearranges the compressed bitstream according to the quality layer and the resolution of the image, and then applies a hierarchical encryption scheme to the reorganized codestream via using cryptographic functions. This supports transparent transcoding operations directly on the compressed and encrypted bitstream. Simulation results demonstrate that the proposed CT-HEA has high transcoding flexibility with a low transcoding costs.

关键词： Encryption Streaming media transcoding Image coding Transform coding

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PROXIMATE CONTROL STREAM ASSISTED VIDEO transcoding FOR HETEROGENEOUS CONTENT DELIVERY NETWORK

PROXIMATE CONTROL STREAM ASSISTED VIDEO TRANSCODING FOR HETE...

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IEEE International Conference on Image Processing

作者： Xuebin Zhang Yiran Li Jiangpeng Li Kai Zhao Tong Zhang ECSE Department Rensselaer Polytechnic Institute NY USA Shanghai Jiao Tong University China

Video transcoding can be used to facilitate video streaming in content delivery network. A concept of control stream assisted transcoding has been recently proposed aiming to reduce transcoding computational complexity at the cost of data storage/transmission overhead, and the control stream is obtained by directly removing the residual information from the target video bitstream of transcoding. However, it is subject to relatively significant storage/transmission overhead, and more importantly does not well match to the increasingly heterogeneous networking environment with varying computation/storage/transmission resources at different nodes. This work presents a proximate control stream assisted transcoding design strategy that can reduce the control stream size and enable a large storage/transmission vs. computational complexity trade-off design space. Experiments demonstrate its effectiveness and noticeable advantages over other alternatives including simulcast and SVC (scalable video coding).

关键词： Syntactics transcoding Vectors Streaming media Indexes Video sequences

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EFFICIENT transcoding FOR SPATIALLY MISALIGNED COMPOSITIONS FOR HEVC

EFFICIENT TRANSCODING FOR SPATIALLY MISALIGNED COMPOSITIONS ...

引用

IEEE International Conference on Image Processing

作者： Johan De Praeter Jan De Cock Glenn Van Wallendael Sebastiaan Van Leuven Peter Lambert Rik Van de Walle Ghent University - iMinds - Multimedia Lab

ISBN: (纸本)9781479957521

The visualization of (ultra) high-resolution compositions created from multiple input bitstreams requires several decoders at the receiving device. Therefore, not all devices can properly display such compositions. To address this problem, the input streams are decoded, merged into a single video, and re-encoded by a transcoder in the network. However, this approach requires a computationally complex re-encoding step. To reduce this complexity, information from the input bit-streams can be reused during transcoding. In HEVC, simply reusing the original encoding information is not compression efficient if the inserted content is not aligned with the grid of coded blocks. In this paper, we applied feature selection based on a decision tree, which was used in a fast HEVC transcoding model for misaligned content. The performance varies depending on the shift and average transform size in the original sequence, resulting in complexity reductions of up to 76%.

关键词： HEVC Picture composition transcoding

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On the Optimal Delay Amplification Factor of Multi-Hop Relay Channels

On the Optimal Delay Amplification Factor of Multi-Hop Relay...

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IEEE International Symposium on Information Theory (ISIT)

作者： Ogbe, Dennis Wang, Chih-Chun Love, David J. Purdue ECE W Lafayette IN 47907 USA

ISBN: (纸本)9781538692912

The abstract model of the multi-hop relay channel is fundamental to a vast variety of modern communication systems. This fact, coupled with the demand for ultra-reliable-low-latency communication (URLLC), motivates a new investigation of relay channels from a delay-vs-throughput perspective. This work seeks to analyze this tradeoff in the regime of asymptotically large, yet still finite delay. A new metric called the Delay Amplification Factor (DAF) is introduced, which allows analytic comparison of the asymptotic delay across different relay solutions, e.g. decode-&-forward (DF), compress-&-forward, etc. The optimal DAF (over all possible existing/future designs) is then characterized for two special settings, one with fixed-length coding and one with variable-length coding and 1-bit stop feedback. The results show that under some general conditions, the optimal end-to-end delay over an L-hop line network is asymptotically comparable to the delay over the single bottleneck hop, and it does not grow linearly with respect to L. The linearly growing delay penalty commonly encountered in DF and other schemes is thus an artifact rather than a fundamental limit of multi-hop relay communication.

关键词： Delays Relays Throughput Spread spectrum communication transcoding Pipeline processing

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CODING TREE EARLY TERMINATION FOR FAST HEVC TRANSRATING BASED ON RANDOM FORESTS 44

CODING TREE EARLY TERMINATION FOR FAST HEVC TRANSRATING BASE...

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44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Bubolz, Thiago Grellert, Mateus Zatt, Bruno Correa, Guilherme Fed Univ Pelotas UFPel Video Technol Res Grp ViTech Pelotas Brazil Catholic Univ Pelotas UCPel Grad Program Elec & Comp Engn Pelotas Brazil

ISBN: (纸本)9781479981311

Video transrating has become an essential task in streaming service providers that need to transmit and deliver different versions of the same content for a multitude of users that operate under different network conditions. As the transrating operation is comprised of a decoding and an encoding step in sequence, a huge computational cost is required in such large-scale services, especially when considering the use of complex state-of-the-art codecs, such as the High Efficiency Video Coding (HEVC). This work proposes an early-termination method for complexity reduction of the HEVC transrating based on Random Forests, which use features obtained from the HEVC decoding process to accelerate the coding tree decisions during the re-encoding process. Experimental results show that the proposed method achieves an average transrating time reduction of 47.09% at the cost of a negligible bitrate increase of 0.292%.

关键词： HEVC transrating transcoding Random Forests

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Catalyst: A Cloud-based Media Processing Framework 39

Catalyst: A Cloud-based Media Processing Framework

引用

39th IEEE International Conference on Distributed Computing Systems (ICDCS)

作者： Katsak, William Nguyen, Hai Nagaraja, Kiran Halen, Joacim Radia, Nimish Nguyen, Thu D. Rutgers State Univ Piscataway NJ 08854 USA Ericsson Res San Jose CA USA Apple Inc Cupertino CA 95014 USA

ISBN: (纸本)9781728125190

Massive increases in production and consumption of digital media are motivating cloud "video encoding as a service." In this paper, we explore efficient platforms for supporting such services. Specifically, we explore transcoding performance on a software encoder and two hardware-accelerated encoders representing widely different points in the hardware acceleration design space, as well as interference effects when heterogenous encoders are run concurrently. Using results from our exploratory study, we next propose a framework for providing video encoding as a service on a single server, and implement a prototype of the framework in a system called Catalyst. Catalyst accepts transcoding tasks and intelligently uses all available resources, including software and hardware-accelerated encoders, to maximize throughput while respecting task deadlines, and provides a foundational building block for a cluster-based cloud video encoding service. We evaluate Catalyst using a synthetic transcoding workload designed to emulate an IP-TV/Cloud-DVR workload. Evaluation results show that Catalyst can significantly increase throughput while meeting task deadlines compared to naive use of hardware-accelerated encoding.

关键词： Software Streaming media transcoding Task analysis Hardware Servers

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Intelligent Edge-Assisted Crowdcast with Deep Reinforcement Learning for Personalized QoE

Intelligent Edge-Assisted Crowdcast with Deep Reinforcement ...

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IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Wang, Fangxin Zhang, Cong Wang, Feng Liu, Jiangchuan Zhu, Yifei Pang, Haitian Sun, Lifeng Simon Fraser Univ Sch Comp Sci Burnaby BC Canada Univ Sci & Technol China Sch Comp Sci & Technol Hefei Anhui Peoples R China Univ Mississippi Dept Comp & Informat Sci University MS 38677 USA Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China

ISBN: (纸本)9781728105154

Recent years have seen booming development and great success in interactive crowdsourced livecast (i.e., crowd cast). Different from traditional livecast services, crowdcast is featured with tremendous video contents at the broadcaster side, highly diverse viewer side content watching environments/preferences as well as viewers' personalized quality of experience (QoE) demands (e.g., individual preferences for streaming delays, channel switching latencies and bitrates). This imposes unprecedented key challenges on how to flexibly and cost-effectively accommodate the heterogeneous and personalized QoE demands for the mass of viewers. In this paper, we propose DeepCast, an edge-assisted crowdcast framework, which makes intelligent decisions at edges based on the massive amount of real-time information from the network and viewers to accommodate personalized QoE with minimized system cost. Given the excessive computation complexity in this context, we propose a data-driven deep reinforcement learning (DRL) based solution that can automatically learn the best suitable strategies for viewer scheduling and transcoding selection. To our best knowledge, DeepCast is the first edge assisted framework that applies the advance of DRL to explicitly accommodate personalized QoE optimization for crowdcast services. We collect multiple real-world datasets and evaluate the performance of DeepCast using trace-driven experiments. The results demonstrate the superiority of our DeepCast framework and its DRL-based solution.

关键词： Quality of experience Servers Bit rate Switches Bandwidth Delays transcoding

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Getting the Most Out of Your VNFs: Flexible Assignment of Service Priorities in 5G 20

Getting the Most Out of Your VNFs: Flexible Assignment of Se...

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20th IEEE International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM)

作者： Malandrino, Francesco Chiasserini, Carla-Fabiana CNR IEIIT Turin Italy Politecn Torino Turin Italy CNIT Pisa Italy

ISBN: (纸本)9781728102702

Through their computational and forwarding capabilities, 5G networks can support multiple vertical services. Such services may include several common virtual (network) functions (VNFs), which could be shared to increase resource efficiency. In this paper, we focus on the seldom studied VNF-sharing problem, and decide (i) whether sharing a VNF instance is possible/beneficial or not, (ii) how to scale virtual machines hosting the VNFs to share, and (iii) the priorities of the different services sharing the same VNF. These decisions are made with the aim to minimize the mobile operator's costs while meeting the verticals' performance requirements. Importantly, we show that the aforementioned priorities should not be determined a priori on a per-service basis, rather they should change across VNFs since such additional flexibility allows for more efficient solutions. We then present an effective methodology called FlexShare, enabling near-optimal VNF-sharing decisions in polynomial time. Our performance evaluation, using real-world VNF graphs, confirms the effectiveness of our approach, which consistently outperforms baseline solutions using per-service priorities.

关键词： Delays transcoding 5G mobile communication Computational modeling Motion detection Face recognition Virtual machining

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