Two-Phase Rate Adaptation Strategy for Improving Real-Time Video QoE in Mobile Networks

With the popularity of smart handheld devices, mobile streaming video has multiplied the global network traffic in recent years. A huge concern of users' quality of experience(Qo E) has made rate adaptation methods very attractive. In this paper, we propose a two-phase rate adaptation strategy to improve users' real-time video Qo E. First, to measure and assess video Qo E, we provide a continuous Qo E prediction engine modeled by RNN recurrent neural network. Different from traditional Qo E models which consider the Qo E-aware factors separately or incompletely, our RNN-Qo E model accounts for three descriptive factors(video quality, rebuffering, and rate change) and reflects the impact of cognitive memory and recency. Besides, the video playing is separated into the initial startup phase and the steady playback phase, and we takes different optimization goals for each phase: the former aims at shortening the startup delay while the latter ameliorates the video quality and the rebufferings. Simulation results have shown that RNN-Qo E can follow the subjective Qo E quite well, and the proposed strategy can effectively reduce the occurrence of rebufferings caused by the mismatch between the requested video rates and the fluctuated throughput and attains standout performance on real-time Qo E compared with classical rate adaption methods.

Real-time Audio &Video Transmission System Based on Visible Light Communication

With the increasing popularity of solid sate lighting devices, Visible Light Communication (VLC) is globally recognized as an advanced and promising technology to realize short-range, high speed as well as large capacity wireless data transmission. In this paper, we propose a prototype of real-time audio and video broadcast system using inexpensive commercially available light emitting diode (LED) lamps. Experimental results show that real-time high quality audio and video with the maximum distance of 3 m can be achieved through proper layout of LED sources and improvement of concentration effects. Lighting model within room environment is designed and simulated which indicates close relationship between layout of light sources and distribution of illuminance.

A Multi-objective QoS Optimization with Fuzzy Based Parameter Setting for Real-Time Multicasting

We propose a multi-objective Pareto-optimal technique using Genetic Algorithm (GA) for group communication, which determines a min-cost multicast tree satisfying end-to-end delay, jitter, packet loss rate and blocking probability constraints. The model incorporates a fuzzy-based selection technique for initialization of QoS parameter values at each instance of multicasting. The simulation results show that the proposed algorithm satisfies on-demand QoS requirements (like high availability, good load balancing and fault-tolerance) made by the hosts in varying topology and bursty data traffic in multimedia communication networks.

Adaptive DirectShow Framework for Layered MPEG-4 Video Multicast

An extensible framework was proposed to implement the hierarchical and adaptive control and feedback mechanism of layered MPEG-4 video multicast transmission in DirectShow architecture. In our framework, layers of MPEG-4 video and FEC data are wrapped dynamically in RTP packets to pass through the heterogeneous network effectively. An adaptive control center is designed to control the actions of the related components dynamically according to varying resources availability on local host and network. This effective and adaptive framework can be used to instruct the implementation of applications based on layered MPEG-4 video multicast transmission and other designs of multimedia application frameworks.

Implementation of IP Multicast in LAN Video Transmission Based on Winsock2

With the development of IP multicast technology, the best use of network bandwidth can be achieved, and IP video broadcasting can be implemented. This paper introduces the principle of IP multicast technology, and presents an implementation of IP video multicasting in LAN based on Winsock2. Problems in IP multicast are also analyzed in brief.

A Novel Video Data-Source Authentication Model Based on Digital Watermarking and MAC in Multicast

A novel video data authentication model based on digital video watermarking and MAC （message authentication code） in multicast protocol is proposed in this paper, The digital watermarking which composes of the MAC of the significant vid eo content, the key and instant authentication data is embedded into the insignificant video component by the MLUT （modified look-up table） video watermarking technology. We explain a method that does not require storage of each data packet for a time, thus making receiver not vulnerable to DOS （denial of service） attack. So the video packets can be authenticated instantly without large volume buffer in the receivers. TESLA （timed efficient stream loss tolerant authentication） does not explain how to select the suitable value for d, which is an important parameter in multicast source authentication. So we give a method to calculate the key disclosure delay （number of intervals）. Simulation results show that the proposed algorithms improve the performance of data source authentication in multicast.

DASH and DASH-VR Video Multicast Systems

Multimedia data traffic occupies more than 70% of the Internet traffic and is still growing. On-demand video is already a major video content platform and private broadcast is getting more popular. In addition to this, virtual reality （VR） and augmented reali- ty （AR） data traffic is increasing very fast. To provide the good quality of the multimediaservice, huge amount of resource is need- ed because users ＇ service experience is usually proportional to the video rates they can receive. Moreover, the variation of the bandwidth also affects to the users＇ experience, w-hile more users w-ant to use their mobile devices to see multimedia data by ac- cessing the network through wireless links, such as Long Term Evolution （LTE） and Wi-Fi. Therefore, better spectral efficiency during wireless transmission and video rate adaptation to provide better quality to users are in great demand. Multicast system is one of the technologies that can improve the spectral efficiency drastically, and Dynamic Adaptive Streaming over HTTP （DASH） is one of the most popular video rate adaptation platforms. In this paper, we investigate the state-of-the-art video multicast technol- ogies. LTE supports the multicast service through evolved Multimedia Broadcast Multicast Service （eMBMS） systems, and there are different algorithms to perform the video multicast along with adaptive video quality control. The algorithms include the proce- dure to decide the video rates, resource allocations, and user groupings. Moreover, we propose a novel approach to improve the quality of experience for DASH-VR video multicast systems.

THE DLSTRIBOTED MCU MODEL FOR SYNCHRONOUS REAL-TIME TELETEACHING

Aiming at issues on multimedia communication in synchronous real-time teleteaching (SRT) systems over IP network, a 4-tuple structural mode of multimedia communication is proposed in the paper, and an SRT-oriented distributed MCU model is built according to the mode. Moreover, the mechanism of multicast communication across subnets is discussed. The distributed MCU model has been applied successfully in our interactive synchronous real-time telesteaching system RealClass and has shown good extendibility in operation.

QoS Aware Multicast Routing Protocol for Video Transmission in Smart Cities

In recent years,Software Defined Networking(SDN)has become an important candidate for communication infrastructure in smart cities.It produces a drastic increase in the need for delivery of video services that are of high resolution,multiview,and large-scale in nature.However,this entity gets easily influenced by heterogeneous behaviour of the user’s wireless link features that might reduce the quality of video stream for few or all clients.The development of SDN allows the emergence of new possibilities for complicated controlling of video conferences.Besides,multicast routing protocol with multiple constraints in terms of Quality of Service(QoS)is a Nondeterministic Polynomial time(NP)hard problem which can be solved only with the help of metaheuristic optimization algorithms.With this motivation,the current research paper presents a new Improved BlackWidow Optimization with Levy Distribution model(IBWO-LD)-based multicast routing protocol for smart cities.The presented IBWO-LD model aims at minimizing the energy consumption and bandwidth utilization while at the same time accomplish improved quality of video streams that the clients receive.Besides,a priority-based scheduling and classifier model is designed to allocate multicast request based on the type of applications and deadline constraints.A detailed experimental analysis was carried out to ensure the outcomes improved under different aspects.The results from comprehensive comparative analysis highlighted the superiority of the proposed IBWO-LD model over other compared methods.

Adaptive Learning Video Streaming with QoE in Multi-Home Heterogeneous Networks

In recent years,real-time video streaming has grown in popularity.The growing popularity of the Internet of Things(IoT)and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience(QoE)and performance objectives.Most researchers focused on Forward Error Correction(FEC)techniques when attempting to strike a balance between QoE and performance.However,as network capacity increases,the performance degrades,impacting the live visual experience.Recently,Deep Learning(DL)algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks.But these algorithms need to be changed to make the experience better without sacrificing packet loss and delay time.To address the previous challenge,this paper proposes a novel intelligent algorithm that streams video in multi-home heterogeneous networks based on network-centric characteristics.The proposed framework contains modules such as Intelligent Content Extraction Module(ICEM),Channel Status Monitor(CSM),and Adaptive FEC(AFEC).This framework adopts the Cognitive Learning-based Scheduling(CLS)Module,which works on the deep Reinforced Gated Recurrent Networks(RGRN)principle and embeds them along with the FEC to achieve better performances.The complete framework was developed using the Objective Modular Network Testbed in C++(OMNET++),Internet networking(INET),and Python 3.10,with Keras as the front end and Tensorflow 2.10 as the back end.With extensive experimentation,the proposed model outperforms the other existing intelligentmodels in terms of improving the QoE,minimizing the End-to-End Delay(EED),and maintaining the highest accuracy(98%)and a lower Root Mean Square Error(RMSE)value of 0.001.

Wireless ad hoc video transmission:a Bayesian network-based scheme

A novel bandwidth prediction and control scheme is proposed for video transmission over an ad boc network. The scheme is based on cross-layer, feedback, and Bayesian network techniques. The impacts of video quality are formulized and deduced. The relevant factors are obtained by a cross-layer mechanism or Feedback method. According to these relevant factors, the variable set and the Bayesian network topology are determined. Then a Bayesian network prediction model is constructed. The results of the prediction can be used as the bandwidth of the mobile ad hoc network （MANET）. According to the bandwidth, the video encoder is controlled to dynamically adjust and encode the right bit rates of a real-time video stream. Integrated simulation of a video streaming communication system is implemented to validate the proposed solution. In contrast to the conventional transfer scheme, the results of the experiment indicate that the proposed scheme can make the best use of the network bandwidth; there are considerable improvements in the packet loss and the visual quality of real-time video.K

无人机辅助智能交通系统中面向视频多播的资源优化

在智能交通系统(Intelligent Transportation System,ITS)中,实时交通视频可以辅助网联车做出更理智的决策。然而,由于车载传感器位置和数量的限制,车辆无法全面掌握交通环境,不利于行车安全;此外,当多个车辆用户请求相同的视频内容时,传统的单播传输模式存在效率低下的问题。为了解决这些问题,基于非正交多址接入(Non-Orthogonal Multiple Access,NOMA)和可伸缩视频编码(Scalable Video Coding,SVC)技术,提出了一种无人机(Unmanned Aerial Vehicle,UAV)辅助ITS的交通视频多播方案。通过联合优化车辆分组和功率分配策略,最大化车辆接收的长期视频质量。将该优化问题建模为一个马尔可夫决策过程(Markov Decision Process,MDP),并采用Soft Actor-Critic(SAC)算法来求解。大量仿真结果表明,该算法具有很强的探索能力,而且收益性能优于传统Actor-Critic(AC)算法。

Interactive transport of multi-view videos for 3DTV applications

The authors propose a novel method for transporting multi-view videos that aims to keep the bandwidth requirements on both end-users and servers as low as possible. The method is based on application layer multicast, where each end point re- ceives only a selected number of views required for rendering video from its current viewpoint at any given time. The set of selected videos changes in real time as the user’s viewpoint changes because of head or eye movements. Techniques for reducing the black-outs during fast viewpoint changes were investigated. The performance of the approach was studied through network experiments.

RTP payload format for H.264/SVC scalable video coding

The scalable extension of H.264/AVC, known as scalable video coding or SVC, is currently the main focus of the Joint Video Team’s work. In its present working draft, the higher level syntax of SVC follows the design principles of H.264/AVC. Self-contained network abstraction layer units (NAL units) form natural entities for packetization. The SVC specification is by no means finalized yet, but nevertheless the work towards an optimized RTP payload format has already started. RFC 3984, the RTP payload specification for H.264/AVC has been taken as a starting point, but it became quickly clear that the scalable features of SVC require adaptation in at least the areas of capability/operation point signaling and documentation of the extended NAL unit header. This paper first gives an overview of the history of scalable video coding, and then reviews the video coding layer (VCL) and NAL of the latest SVC draft specification. Finally, it discusses different aspects of the draft SVC RTP payload format, in- cluding the design criteria, use cases, signaling and payload structure.

Design and implementation of multi-hop video transmission experiment system in VANET

Abts ract A wireless mutl i-hop videot ransmission experiment system is designed and implemented for vehiculra ad-hoc networks VANET and the rt ansm ission control protocol and routing protocol are proposed. This system in tegrates the embedded Linux system witha n ARM kernel and oc ns ists of a S3C6410 main control module a wirel ss local arean etwork WLAN card a LCD screne and so on.In the scenario of a wireless multi-hop video transmission both the H.264 and JPEG are used and their performances such as the compression rate delay and frame loss rate are analyzed in theory andc ompared in the experiment.The system is tested in the real indoor and outdoor environment.The results show that the scheme of the multi-hop video transmission experiment system can be applicable for VANET and multiple scenes and the transmission control protocol and routing protocol proposed can achieve real-time transmission and meet multi-hop requirements.

A Centralized Algorithm for Assigning MDC Video Application in Virtual Network

Providing services on demand is a major contributing factor to drive the increasingly development of the software defined network. However, it should supply all the current popular applications before it really attains widespread development. Multiple Description Coding(MDC) video applications, as a popular application in the current network, should be reasonably supported in this novel network virtualization environment. In this paper, we address this issue to assign MDC video application into virtual networks with an efficient centralized algorithm(CAMDV). Since this problem is an NP-hard problem, we design an algorithm that can effectively balance the user satisfaction and network resource cost. Previous work just builds a global multicast tree for each description to connect all the destination nodes by breadth-first search strategy or shortest path tree algorithm. But those methods could not achieve an optimal balance or a high-level user satisfaction. By introducing the hierarchical clustering scheme, our algorithm decomposes the whole mapping procedure into multicast tree construction and multipath description distribution. A serial of simulation experiments show that our centralized algorithm could achieve a better performance in balancing the user satisfaction and average mapping cost in comparison with its rivals.

View Direction Adaptive 360 Degree Video Streaming System Based on Projected Area

360 video streaming services over the network are becoming popular. In particular, it is easy to experience 360 video through the already popular smartphone. However, due to the nature of 360 video, it is difficult to provide stable streaming service in general network environment because the size of data to send is larger than that of conventional video. Also, the real user's viewing area is very small compared to the sending amount. In this paper, we propose a system that can provide high quality 360 video streaming services to the users more efficiently in the cloud. In particular, we propose a streaming system focused on using a head mount display (HMD).

Performance Analysis of Hybrid RR Algorithm for Anomaly Detection in Streaming Data

Automated live video stream analytics has been extensively researched in recent times.Most of the traditional methods for video anomaly detection is supervised and use a single classifier to identify an anomaly in a frame.We propose a 3-stage ensemble-based unsupervised deep reinforcement algorithm with an underlying Long Short Term Memory(LSTM)based Recurrent Neural Network(RNN).In the first stage,an ensemble of LSTM-RNNs are deployed to generate the anomaly score.The second stage uses the least square method for optimal anomaly score generation.The third stage adopts award-based reinforcement learning to update the model.The proposed Hybrid Ensemble RR Model was tested on standard pedestrian datasets UCSDPed1,USDPed2.The data set has 70 videos in UCSD Ped1 and 28 videos in UCSD Ped2 with a total of 18560 frames.Since a real-time stream has strict memory constraints and storage issues,a simple computing machine does not suffice in performing analytics with stream data.Hence the proposed research is designed to work on a GPU(Graphics Processing Unit),TPU(Tensor Processing Unit)supported framework.As shown in the experimental results section,recorded observations on framelevel EER(Equal Error Rate)and AUC(Area Under Curve)showed a 9%reduction in EER in UCSD Ped1,a 13%reduction in ERR in UCSD Ped2 and a 4%improvement in accuracy in both datasets.

Augmented virtual environment: fusion of real-time video and 3D models in the digital earth system

An Augmented virtual environment(AVE)is concerned with the fusion of real-time video with 3D models or scenes so as to augment the virtual environment.In this paper,a new approach to establish an AVE with a wide field of view is proposed,including real-time video projection,multiple video texture fusion and 3D visualization of moving objects.A new diagonally weighted algorithm is proposed to smooth the apparent gaps within the overlapping area between the two adjacent videos.A visualization method for the location and trajectory of a moving virtual object is proposed to display the moving object and its trajectory in the 3D virtual environment.The experimental results showed that the proposed set of algorithms are able to fuse multiple real-time videos with 3D models efficiently,and the experiment runs a 3D scene containing two million triangles and six real-time videos at around 55 frames per second on a laptop with 1GB of graphics card memory.In addition,a realistic AVE with a wide field of view was created based on the Digital Earth Science Platform by fusing three videos with a complex indoor virtual scene,visualizing a moving object and drawing its trajectory in the real time.