With the increase in the bandwidth & the transmission speed over the internet, transmission of multimedia objects like video, audio, images has become an easier work. In this paper we provide an approach that can be useful for transmission of video objects over the internet without much fuzz. The approach provides a ontology based framework that is used to establish an automatic deployment of video transmission system. Further the video is compressed using the structural flow mechanism that uses the wavelet principle for compression of video frames. Finally the video transmission algorithm known as RRDBFSF algorithm is provided that makes use of the concept of restrictive flooding to avoid redundancy thereby increasing the efficiency.
The significant increase of the transmission of multimedia content over Internet are demanded new delivery strategies to assure a good quality of experience of the users. Transmission of video over packet networks is not an easy task due to multiple fluctuations of the network conditions. One possibility to improve the quality of some video streaming services is the combinate use of the scalable video coding and cross layer mechanisms that allow applications to adapt its traffic stream to the resources network that are available. In this paper, it is presented a performance evaluation of the t…
In recent network architectures, multi-MEC cooperative caching has been introduced to reduce the transmission latency of VR videos, in which MEC servers' computing and caching capability are utilized to optimize the transmission process. However, many solutions that use the computing capability of MEC servers ignore the additional arithmetic power consumed by the codec process, thus making them infeasible. Besides, the minimum cache unit is usually the entire VR video, which makes caching inefficient. To address these challenges, we split VR videos into tile files for caching based on the curr…
Mobile cloud gaming enables high-end games on constrained devices by streaming the game content from powerful servers through mobile networks. Mobile networks suffer from highly variable bandwidth, latency, and losses that affect the gaming experience. This paper introduces Nebula, an end-to-end cloud gaming framework to minimize the impact of network conditions on the user experience. Nebula relies on an end-to-end distortion model adapting the video source rate and the amount of frame-level redundancy based on the measured network conditions. As a result, it minimizes the motion-to-photon (M…
COMETS: Coordinated Multi-Destination Video Transmission with In-Network Rate Adaptation
The Hong Kong University of Science and Technology, Guangzhou（香港科技大学（广州））；The Hong Kong University of Science and Technology（香港科技大学）；University of Jyväskylä（于韦斯屈莱大学）
The pseudo-analog wireless video transmission technology can improve the effectiveness, reliability, and robustness of the conventional digital system in video broadcast scenarios. Although some prototypes of IEEE 802.11 series have been developed for researchers to do simulations and experiments, they are usually expensive and provide very limited access to the physical layer. More importantly, these prototypes cannot be used to verify the correctness of the new proposed pseudo-analog wireless video transmission algorithms directly due to limited modulation modes they can support. In this pap…
Video transmission over the backhaul link in cloud-edge collaborative networks usually suffers security risks, which is ignored in most of the existing studies. The characteristics that video service can flexibly adjust the encoding rates and provide acceptable encoding qualities, make the security requirements more possible to be satisfied but tightly coupled with video encoding by introducing more restrictions on edge caching. In this paper, by considering the interaction between video encoding and edge caching, we investigate the quality of experience (QoE)-driven cross-layer optimization o…
In this paper, we study the optimal transmission of a multi-quality tiled 360 virtual reality (VR) video from a multi-antenna server (e.g., access point or base station) to multiple single-antenna users in a multiple-input multiple-output (MIMO)-orthogonal frequency division multiple access (OFDMA) system. We minimize the total transmission power with respect to the subcarrier allocation constraints, rate allocation constraints, and successful transmission constraints, by optimizing the beamforming vector and subcarrier, transmission power and rate allocation. The formulated resource allocatio…
With the dramatically increasing video streaming in the total network traffic, it is critical to develop effective algorithms to promote the content delivery service of high quality. Adaptive bitrate (ABR) control is the most essential technique which determines the proper bitrate to be chosen based on network conditions, thus realize high-quality video streaming. In this paper, a novel ABR strategy is proposed based on Ising machine by using the quadratic unconstrained binary optimization (QUBO) method and Digital Annealer (DA) for the first time. The proposed method is evaluated by simulatio…
The paper deals with Video Coding for Machines that is a new paradigm in video coding related to consumption of decoded video by humans and machines. For such tasks, joint transmission of compressed video and features is considered. In this paper, we focus our considerations of features on SIFT keypoints. They can be extracted from the decoded video with losses in number of keypoints and their parameters as compared to the SIFT keypoints extracted from the original video. Such losses are studied for HEVC and VVC as functions of the quantization parameter and the bitrate. In the paper, we propo…
Video transmission services adopt adaptive algorithms to ensure users' demands. Existing techniques are often optimized and evaluated by a function that linearly combines several weighted metrics. Nevertheless, we observe that the given function fails to describe the requirement accurately. Thus, such proposed methods might eventually violate the original needs. To eliminate this concern, we propose \emph{Zwei}, a self-play reinforcement learning algorithm for video transmission tasks. Zwei aims to update the policy by straightforwardly utilizing the actual requirement. Technically, Zwei sampl…
Omnidirectional applications are immersive and highly interactive, which can improve the efficiency of remote collaborative work among factory workers. The transmission of omnidirectional video (OV) is the most important step in implementing virtual remote collaboration. Compared with the ordinary video transmission, OV transmission requires more bandwidth, which is still a huge burden even under 5G networks. The tile-based scheme can reduce bandwidth consumption. However, it neither accurately obtain the field of view(FOV) area, nor difficult to support real-time OV streaming. In this paper, …
In traditional communication system, information of APP (Application) layer, transport layer and MAC (Media Access Control)layer has not been fully interacted,which inevitably leads to inconsistencies among TCP congestion state, clients'requirements and resource allocation. To solve the problem, we propose a joint optimization framework, which consists of APP layer, transport layer and MAC layer, to improve the video clients'playback experience and system throughput. First, a client requirement aware autonomous packet drop strategy, based on packet importance, channel condition and playback st…
Recently, pseudo analog transmission has gained increasing attentions due to its ability to alleviate the cliff effect in video multicast scenarios. The existing pseudo analog systems are sorely optimized under the minimum mean squared error criterion without taking the perceptual video quality into consideration. In this paper, we propose a human-perception-based pseudo analog video transmission system named ROIC-Cast, which aims to intelligently enhance the transmission quality of the region-of-interest (ROI) parts. Firstly, the classic deep learning based saliency detection algorithm is ado…
We present DeepWiVe, the first-ever end-to-end joint source-channel coding (JSCC) video transmission scheme that leverages the power of deep neural networks (DNNs) to directly map video signals to channel symbols, combining video compression, channel coding, and modulation steps into a single neural transform. Our DNN decoder predicts residuals without distortion feedback, which improves video quality by accounting for occlusion/disocclusion and camera movements. We simultaneously train different bandwidth allocation networks for the frames to allow variable bandwidth transmission. Then, we tr…
WVSC: Wireless Video Semantic Communication with Multi-frame Compensation
Department of Electronic Engineering, Shanghai Jiao Tong University（上海交通大学电子工程系）；School of Cyber and Engineering, Shanghai Jiao Tong University（上海交通大学网络与工程学院）；ISTD Pillar, Singapore University of Technology of Design（新加坡科技设计大学ISTD支柱）
Wireless Video Semantic Communication with Decoupled Diffusion Multi-frame Compensation
Department of Electronic Engineering, Shanghai Jiao Tong University（电子工程系，上海交通大学）；School of Cyber and Engineering, Shanghai Jiao Tong University（网络与工程学院，上海交通大学）；ISTD Pillar, Singapore University of Technology of Design（新加坡设计大学技术支柱）
School of Electrical Engineering and Automation, Hefei University of Technology, and Engineering Technology Research Center of Industrial Automation Anhui Province, Hefei, Anhui 230009, China（合肥工业大学电气与自动化学院，安徽省工业自动化工程技术研究中心）；The University of Electro-Communications, Tokyo, Japan（东京电讯大学）；School of Computer Science and Technology, University of Science and Technology of China, Hefei, China（中国科学技术大学计算机科学与技术学院）；Department of Electrical and Computer Engineering, Aarhus University, Aarhus, Denmark（哥本哈根大学电子与计算机工程系）；Department of Computer Science and Electrical Engineering, University of Missouri–Kansas City, Kansas, USA（密苏里大学- Kansas 城市分校计算机科学与电气工程系）；School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China（合肥工业大学计算机科学与信息工程学院）
Shandong University（山东大学）；National University of Singapore（新加坡国立大学）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））；Kuaishou Technology（快手科技）
The last decade has witnessed the proliferation of micro-videos on various user-generated content platforms. According to our statistics, around 85.7\% of micro-videos lack annotation. In this paper, we focus on annotating micro-videos with tags. Existing methods mostly focus on analyzing video content, neglecting users' social influence and tag relation. Meanwhile, existing tag relation construction methods suffer from either deficient performance or low tag coverage. To jointly model social influence and tag relation, we formulate micro-video tagging as a link prediction problem in a constru…
