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IEEE International Conference on Communications (ICC)

作者： Yi-Pao Wu Cheng-Yeh Chen Tsung-Yu Li Hung-Yun Hsieh Graduate Institute of Communication Engineering Department of Electrical Engineering National Taiwan University Taipei Taiwan School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Current wireless volumetric video streaming faces multiple challenges, including high bandwidth consumption, large decoding overhead on the client device, and low view reconstruction quality perceived by the user. In this paper, we explore an edge-assisted streaming system, where 3D contents of volumetric video are first transcoded by the edge server based on predicted user positions and then transmitted to the client to substantially reduce the bandwidth consumption and decoding overhead. In such a system, however, inaccuracy in position prediction could lead to displacement between the transcoded reference view and the actual view required by the client. To mitigate this problem, we task the edge server to transcode multiple views and formulate the problem of multiview generation as an optimal quantization problem. Rather than using distance-based distortion metrics, our formulation considers the actual distortion perceived by the user for solving the general problem of positioning reference views under general position error distribution caused by position predictors. Our evaluations show significant improvements over state-of-the-art techniques by reducing quality degradation from 17% to 28% in terms of the 75-th and 95-th percentiles of distortion perceived by users.

关键词： Wireless communication Three-dimensional displays Quantization (signal) Bandwidth transcoding Streaming media Distortion

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Boosting Edge-to-Cloud Data Transmission Efficiency with Semantic transcoding

Boosting Edge-to-Cloud Data Transmission Efficiency with Sem...

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Canadian Conference on Electrical and Computer Engineering (CCECE)

作者： Murtadha Nisyif Ahmed Refaey Sylvester Aboagye University of Guelph Guelph Canada

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

The evolution of network systems is driven by the increasing demand for higher data transmission volumes and reduced latency. This paper presents a semantic method to reduce latency in core network systems to accommodate the growing demand for high-speed data transmission. We minimize unnecessary transmissions and optimize bandwidth by prioritizing data relevance through semantic communication technologies. Our approach utilizes a transformer-based model from edge servers to the cloud to achieve minimal end-to-end latency. Experimental results demonstrate that our methods can reduce latency by up to 30%, offering a scalable solution that significantly enhances network performance and efficiency.

关键词： Solid modeling Semantics transcoding Bandwidth Transformer cores Transformers Communications technology

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Experimental Demonstration of Optical transcoding of 5-Gbit/s OOK Data Signal by Recovering One of the Two Channels of 10-Gbit/s QPSK Data Signal Using Wave-Mixing

Experimental Demonstration of Optical Transcoding of 5-Gbit/...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Narek Karapetyan Amir Minoofar Abdulrahman Alhaddad Wing Ko Huibin Zhou Muralekrishnan Ramakrishnan Moshe Tur Jonathan L. Habif Alan E. Willner Depart. of Electrical Engineering University of Southern California Los Angeles USA School of Electrical Engineering Tel Aviv University Ramat Aviv Israel University of Southern California Information Sciences Institute 890 Winter St. Waltham USA Dornsife Depart. of Physics & Astronomy University of Southern California Los Angeles USA

We demonstrate optical transcoding of 5-Gbit/s OOK data signal from 10-Gbit/s QPSK data signal. A BPSK signal is first generated by constellation squeezing through four-wave-mixing, and then it is shifted to the OOK s... 详细信息

ISBN: (纸本)9798350369311

关键词： transcoding Lasers and electrooptics Vectors Binary phase shift keying Electro-optical waveguides

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Performance Analysis of Random Forest and K-nearest Neighbour for Prediction of Video transcoding Time

Performance Analysis of Random Forest and K-nearest Neighbou...

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2024 1st International Conference on Logistics (ICL)

作者： Asaju La'aro Bolaji Moshood A. Hambali Amakundi Samuel Bako Abdulwahab Ali A. Almazroi Department of Computer Science Federal University Wukari Wukari Taraba State Nigeria Department of Information Technology College of Computing and Information Technology at Khulais University of Jeddah Saudi Arabia

ISBN: (数字)9798331518844

ISBN: (纸本)9798331518851

Currently, the distribution of video content to numerous devices via different communication networks cannot be over-emphasized. This distribution must be adjusted to the resolution, size of the screen, bandwidth availability, and the decoding power of the final user gadgets. This paper studied the effectiveness of the Random Forest and K-Nearest Neighbour for predicting the video transcoding time. Video transcoding executes several tasks which include format conversions and bit rate readjustment, to convert one video stream compression to another. transcoding helps diverse media with different devices formats and capabilities to exchange video content on heterogeneous network platforms such as the Internet. The two algorithmic models predict the time of transcoding of video segments for the codecs using the transcoding parameters and content complexity. The performance of the proposed random forest and KNN is evaluated using online video characteristics and transcoding. Experimental results showed Random forest outperforms the KNN in all the metrics utilized. Furthermore, the Random Forest is better in terms of performance when compared with other approaches available in the literature with a very low MAE of 0.809 and had a competitive performance in $R^{2}$ .

关键词： Performance evaluation Machine learning algorithms Accuracy transcoding Computer architecture Streaming media Nearest neighbor methods Prediction algorithms Internet Random forests

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Joint Transmission and transcoding in Computing Power Networks for Livecast: A Quantum-inspired Optimization Approach

Joint Transmission and Transcoding in Computing Power Networ...

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IEEE Conference on Wireless Communications and Networking

作者： Xin Zou Renchao Xie Qinqin Tang Tao Huang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing P. R.China Purple Mountain Laboratories Nanjing P.R. China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

With the continuous development of network technology and hardware devices, panoramic live cast is promising and widely used in various industries. To meet massive heterogeneous viewer demands, live cast video streams must be transcoded into multiple versions and then transmitted to viewers. By offloading transcoding workloads to network nodes closer to broadcasters and viewers, computing power networks (CPN) have been considered an effective means to provide viewers with a higher quality of experience (QoE). In this paper, we study the joint video transmission and transcoding resource allocation in the CPN-based panoramic livecast system. Considering the versatility and simplicity, we offer a multi-layer network model to capture the stochastic characteristics of transmission and transcoding processes and transform the joint resource allocation problem into a broader shortest path problem (SPP). As the scale of networks expands, the SPP may become intractable on classical computers. This paper explores the viability of solving the SPP on quantum computers by utilizing quantum resources such as superposition and entanglement, then proposes a shortest path algorithm based on the quantum approximate optimization algorithm (QAOA-SPP) for jointly optimizing the latency and overhead of transmission and transcoding. Simulation results indicate that our algorithm can achieve better performance than the benchmark schemes under reasonable parameter settings.

关键词： Computers Quantum computing Quantum entanglement Computational modeling transcoding Transforms Approximation algorithms

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On-the-Fly Edge transcoding for Interactive VR

On-the-Fly Edge Transcoding for Interactive VR

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Andreas Casparsen Federico Chiariotti Jimmy Jessen Nielsen Department of Electronic Systems Aalborg University Denmark

The recent rise of the Cloud Virtual Reality (VR) paradigm, in which VR frames are streamed from a remote server to the user's Head-Mounted Display (HMD), poses some interesting challenges from a networking perspective. VR flows are high-throughput and have strict latency requirements. In this paper, we analyze on-the-fly edge transcoding, which follows the opposite philosophy from the more common slicing approach: instead of adapting resource allocation to the content, we compress the frames to fit into the allocated bandwidth, guaranteeing limited latency. Our results show that this strategy is effective in maintaining low latency, but the picture quality is highly dependent on the computing power of the Base Station (BS).

关键词： Cloud computing Base stations Philosophical considerations Head-mounted displays transcoding Virtual reality Resists

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Fast Rules to Speedup HEVC to VVC transcoding 25

Fast Rules to Speedup HEVC to VVC Transcoding

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25th Pan-Hellenic Conference on Informatics with International Participation (PCI)

作者： Panagou, Natalia Belememis, Panagiotis Papadopoulos, Panos K. Koziri, Maria Loukopoulos, Thanasis Univ Thessaly Lamia Greece

ISBN: (纸本)9781450395557

With the advent of the newly introduced Versatile Video Coding Standard (VVC) the need for converting legacy content from its widely used predecessor, High Efficiency Video Coding (HEVC), to the new format has emerged due to the higher compression performance of the new codec. The most straightforward transcoding solution is to fully decode and re-encode the incoming video signal to the new coding format, in other respects a notably time-consuming operation. In this paper, we propose a fast HEVC to VVC transcoding algorithm that exploits the high correlation between block partitioning decisions in HEVC and VVC in order to early terminate the block partitioning process in VVC and consequently reduce the transcoding time complexity.

关键词： vvc hevc video coding transcoding complexity reduction

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A Universal transcoding and Transmission Method for Livecast with Networked Multi-Agent Reinforcement Learning 40

A Universal Transcoding and Transmission Method for Livecast...

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40th IEEE Conference on Computer Communications (IEEE INFOCOM)

作者： Chen, Xingyan Xu, Changqiao Wang, Mu Wu, Zhonghui Yang, Shujie Zhong, Lujie Muntean, Gabriel-Miro Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Capital Normal Univ Beijing 100048 Peoples R China Dublin City Univ Sch Elect Engn Dublin 9 Ireland

ISBN: (纸本)9780738112817

Intensive video transcoding and data transmission are the most crucial tasks for large-scale Crowd-sourced Livecast Services (CLS). However, there exists no versatile model for joint optimization of computing resources (e.g., CPU) and transmission resources (e.g., bandwidth) in CLS systems, making maintaining the balance between saving resources and improving user viewing experience very challenging. In this paper, we first propose a novel universal model, called Augmented Graph Model (AGM), which converts the above joint optimization into a multi-hop routing problem. This model provides a new perspective for the analysis of resource allocation in CLS, as well as opens new avenues for problem-solving. Further, we design a decentralized Networked Multi-Agent Reinforcement Learning (MARL) approach and propose an actor-critic algorithm, allowing network nodes (agents) to distributively solve the multi-hop routing problem using AGM in a fully cooperative manner. By leveraging the computing resource of massive nodes efficiently, this approach has good scalability and can be employed in large-scale CLS. To the best of our knowledge, this work is the first attempt to apply networked MARL on CLS. Finally, we use the centralized (single-agent) RL algorithm as a benchmark to evaluate the numerical performance of our solution in a large-scale simulation. Additionally, experimental results based on a prototype system show that our solution is superior in saving resources and service performance to two alternative state-of-the-art solutions.

关键词： Computational modeling Scalability Prototypes transcoding Reinforcement learning Spread spectrum communication Routing

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Joint Scalable Video Coding and transcoding Solutions for Fog-Computing-Assisted DASH Video Applications

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FUTURE INTERNET 2022年第9期14卷 268-268页

作者： Nafeh, Majd Bozorgchenani, Arash Tarchi, Daniele Univ Bologna Dept Elect Elect & Informat Engn Guglielmo Marcon I-40121 Bologna Italy Univ Lancaster Sch Comp & Commun Lancaster LA1 4YQ England

Video streaming solutions have increased their importance in the last decade, enabling video on demand (VoD) services. Among several innovative services, 5G and Beyond 5G (B5G) systems consider the possibility of providing VoD-based solutions for surveillance applications, citizen information and e-tourism applications, to name a few. Although the majority of the implemented solutions resort to a centralized cloud-based approach, the interest in edge/fog-based approaches is increasing. Fog-based VoD services result in fulfilling the stringent low-latency requirement of 5G and B5G networks. In the following, by resorting to the Dynamic Adaptive Streaming over HTTP (DASH) technique, we design a video-segment deployment algorithm for streaming services in a fog computing environment. In particular, by exploiting the inherent adaptation of the DASH approach, we embed in the system a joint transcoding and scalable video coding (SVC) approach able to deploy at run-time the video segments upon the user's request. With this in mind, two algorithms have been developed aiming at maximizing the marginal gain with respect to a pre-defined delay threshold and enabling video quality downgrade for faster video deployment. Numerical results demonstrate that by effectively mapping the video segments, it is possible to minimize the streaming latency while maximising the users' target video quality.

关键词： fog computing DASH scalable video coding transcoding

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transcoding counts: Longitudinal contribution of number writing to arithmetic in different languages

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JOURNAL OF EXPERIMENTAL CHILD PSYCHOLOGY 2022年 223卷 105482页

作者： Banfi, Chiara Clayton, Francina J. Steiner, Anna F. Finke, Sabrina Kemeny, Ferenc Landerl, Karin Gobel, Silke M. Karl Franzens Univ Graz Inst Psychol A-8010 Graz Austria Med Univ Graz Inst Med Informat Stat & Documentat A-8036 Graz Austria Univ York Dept Psychol York YO10 5DD England Univ Appl Sci FH JOANNEUM A-8020 Graz Austria Eotvos Lorand Univ Inst Educ & Psychol Szombathely H-1075 Budapest Hungary BioTechMed Graz A-8010 Graz Austria Macquarie Univ Dept Cognit Sci Sydney NSW 2109 Australia Univ Oslo Dept Special Needs Educ N-0318 Oslo Norway

Number writing involves transcoding from number words (e.g., "thirty-two") to written digit strings (32) and is an important unique predictor of arithmetic. The existing longitudinal evidence about the relation between transcoding and arithmetic is mostly language specific. In languages with number word inversion (e.g., German), the order of tens and units is transposed in spoken num-ber words compared with Arabic numbers. This makes transcoding more challenging than in languages without number word inver-sion (e.g., English). In the current study, we aimed to understand whether the contribution of number writing to the development of arithmetic is similar in languages with and without number word inversion. German-speaking children (n = 166) and English-speaking children (n = 201) were followed over the first 3 years of primary school. In a series of multiple linear regressions, we tested whether number writing of multi-digit numbers was a significant unique predictor of arithmetic after controlling for well-known non-numerical predictors (nonverbal reasoning and working memory) and numerical predictors (symbolic and

关键词： Arithmetic Coss -linguistic comparison Longitudinal study Number processing Number writing transcoding

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