Video Streaming System Research Articles

Selecting Method of Sending Block Images Based on Time-Domain Frequency Estimation for Low Delay Live Video Streaming System

To realize low delay live video streaming system over lossy network, each captured frame must be divided into block images, and these images must be encoded, packetized, and sent selectively. To improve the quality of reproduced frames at the receiver side, the selecting method of the block images must be sophisticated. This paper proposed an optimal selecting method of block images. The method consists of three phases based on the formulated two optimization problems. Firstly, a frequency analysis method is applied to the recent luminance value for each block area. Secondly, sendable block ratio is optimally distributed among block areas based on the result of frequency analysis to satisfy the available bandwidth condition. Finally, the optimal timings of sending are planned for each block area to minimize the error of reproduced image under the condition of assigned sendable block ratio. Some experiments were conducted to evaluate the proposed method using three frequently used reference video sequences. The results of comparison with the conventional method shows that the proposed method improved the mean squared error (MSE) of reproduced image up to 64%. Another results shows that the robustness of the proposed method against packet loss can be changed by modifying the parameter of the optimization problem.

Real-time and smooth scalable video streaming system with bitstream extractor intellectual property implementation

Network congestion causes the users cannot perform a real-time streaming service. The paper proposes a real-time and smooth scalable video coding (SVC) streaming system with a bitstream extractor intellectual property (BEIP) design. The system parses the source video to obtain the video information, moreover, adjusts adaptively streaming resolution for limited network bandwidth. The BEIP with very large scale integration (VLSI) implementation, the speed, power consumption, and chip area are 243MHz, 25mW and 1.073×1.028mm2, respectively. The IP performs high system throughput of 7.8Gbps to deal with the network traffic.

PERANCANGAN DAN ANALISA PERBANDINGAN ANTARA DELAY DAN THROUGHPUT PADA VIDEO STREAMING MENGGUNAKAN IPv4 DAN IPv6 TUNNELING

Along with the rapid growth of the Internet, causing problem in the allocation of IPv4 addressing. Therefore, IPv4 only have less than 4 billion addresses and will soon be exhausted. Therefore, IPv6 has been created and used hexadecimal system on it addressing and has very large address allocation that is 3,4 x 1038 addresses. But now many network infrastructures in terms of hardware and software that have not fully support IPv6. So, the devices that still using IPv4 can through IPv6-based network infrastructures, they can use tunneling technique. This makes the emergence of the idea to test the delay and throughput in streaming video system which has a heavy workload on the network. Video streaming system on Vision 1.0 application takes advantage motor stepper webcam in order to support the visibility of the image that can be captured. Then the client who connected to the server can control remotely the motor stepper webcam. On the implementation phase, Vision 1.0 is running on IPv4 and IPv6 network. Next on the testing phase, carried out delay and throughput data collections from those both network systems. From the obtained results in testing, showed no significant difference. So, in general, the performance difference is not too pronounced when the video streaming system is running on both network systems. However, from a comparison based on mean value of delay and throughput, IPv4 is still superior due to the header of the data packet does not as big asIPv6 header which of course affects the packet data frame size, then the traffic network more crowded.

Low-Cost Eye Gaze Prediction System for Interactive Networked Video Streaming

Eye gaze is now used as a content adaptation trigger in interactive media applications, such as customized advertisement in video, and bit allocation in streaming video based on region-of-interest (ROI). The reaction time of a gaze-based networked system, however, is lower-bounded by the network round trip time (RTT). Furthermore, only low-sampling-rate gaze data is available when commonly available webcam is employed for gaze tracking. To realize responsive adaptation of media content even under non-negligible RTT and using common low-cost webcams, we propose a Hidden Markov Model (HMM) based gaze-prediction system that utilizes the visual saliency of the content being viewed. Specifically, our HMM has two states corresponding to two of human's intrinsic gaze behavioral movements, and its model parameters are derived offline via analysis of each video's visual saliency maps. Due to the strong prior of likely gaze locations offered by saliency information, accurate runtime gaze prediction is possible even under large RTT and using common webcam. We demonstrate the applicability of our low-cost gaze prediction system by focusing on ROI-based bit allocation for networked video streaming. To reduce transmission rate of a video stream without degrading viewer's perceived visual quality, we allocate more bits to encode the viewer's current spatial ROI, while devoting fewer bits in other spatial regions. The challenge lies in overcoming the delay between the time a viewer's ROI is detected by gaze tracking, to the time the effected video is encoded, delivered and displayed at the viewer's terminal. To this end, we use our proposed low-cost gaze prediction system to predict future eye gaze locations, so that optimized bit allocation can be performed for future frames. Through extensive subjective testing, we show that bit-rate can be reduced by up to 29% without noticeable visual quality degradation when RTT is as high as 200 ms.

A DHT-Aided Chunk-Driven Overlay for Scalable and Efficient Peer-to-Peer Live Streaming

Internet-based video streaming applications are becoming more and more popular, attracting millions of online viewers every day. The incredible growth of viewers, dynamics of participants, and high video quality of service (QoS) requirement pose scalability, availability, and low-latency challenges to peer-to-peer (P2P) live video streaming systems. Tree-based systems have low-delay but are vulnerable to churn, while mesh-based systems are churn-resilient but suffer from high delay and overhead. Also, both structures cannot make full utilization of the bandwidth in the system. To tackle the challenges, we propose a DHT-aided chunk-driven overlay (DCO). It introduces a scalable DHT ring structure into a mesh-based overlay to efficiently manage video stream sharing. DCO includes a two-layer hierarchical DHT-based infrastructure, a chunk sharing algorithm, and a video provider selection algorithm. It selects stable nodes to form a scalable DHT-based infrastructure. The nodes in the DHT serve as distributed matchmakers between video providers and requesters. To motivate stable nodes to serve as the DHT nodes, we introduce an incentive mechanism based on the game theory. Aided by DHT, DCO guarantees stream chunk availability and assigns to a chunk requester a provider among all available providers in the system so that stream chunks are transmitted along a dynamic tree with top-down decreasing node bandwidth. In this way, DCO takes full advantage of available bandwidth in the system and, at the same time, provides high scalability and low latency. Experimental results show the superior performance of DCO compared with mesh-based and tree-based systems, and the effectiveness of the incentive mechanism and provider selection algorithm.

Liquidstream II—Scalable P2P overlay optimization with adaptive minimal server assistance for stable and efficient video on demand

In recent years, a number of research efforts have focused on effective and stable P2P architectures aiming at large scale and low bandwidth cost, real time video streaming systems. Particularly, live streaming and Video-on-Demand (VoD) systems have lately attracted much interest. While many efforts mainly focused on the development of distributed schedulers for content exchange among the participating peers, there are still open fundamental questions regarding the graph (P2P overlay) structure that determines the set of peers with which each peer communicates. Additionally, the way that cloud media servers support these systems is still an open issue. In this paper, we consider a BitTorrent-like VoD system and focus on the following questions: (1) how a distributed-scalable architecture can be formed in a highly heterogeneous and dynamic environment such that it dynamically manages the P2P overlay by means of exploiting the available upload bandwidth of the participating peers, and (2) how a cloud media (bandwidth provider) server reduces the amount of the bandwidth percentage contributed to the system in order to support a larger number of peers. To illustrate the success of our approach, we have developed an extensive P2P VoD simulator for demonstrating the efficiency, scalability and stability of our work under variant and dynamic conditions. Our system guarantees the uninterrupted and efficient video distribution, even in extreme cases of peer arrivals and departures at high rates.

QoS-supporting video streaming system with minimum data service cost over heterogeneous wireless networks

This paper presents a video streaming system that supports quality-of-service by effectively consolidating multiple physical paths in a cost-effective way over heterogeneous wireless networks. In the proposed system, the fountain encoding symbols of compressed video data are transmitted through multiple physical paths concurrently to overcome the limitation of single path transmission and harmonize multiple physical paths with diverse characteristics effectively, and the number of transmitted packets is determined by considering the requested quality-of-service of video streaming and the data service cost. The proposed system is fully implemented in Java and C/C++, and tested over real WLAN and LTE networks. Experimental results are provided to demonstrate the performance improvement of the proposed system.

A Real-Time Error Resilient Video Streaming Scheme Exploiting the Late- and Early-Arrival Packets

For real-time video streaming systems, the video packets arriving after the display deadline of their frames are considered as late-arrival packets, and typically they are discarded. This will affect the current frame and the following ones due to error propagations. For this reason, in this paper, we propose an approach to exploit the late-arrival and out-of-order packets, which includes two mechanisms. The first mechanism will use these packets to update the reference frames to make them more consistent with the encoder side, and this will eventually reduce the error propagations. The second mechanism will use these packets to increase the chance of successfully decoding the Reed-Solomon (RS) code. In the proposed approach, a sub-GOP based systematic RS code is used and optimized to exploit these packets, where the size of each sub-GOP and the parity packet number for each sub-GOP are optimally tuned, taking into consideration the maximum end-to-end delay, the network conditions, and other system parameters, so as to make the best use of the late-arrival packets and to exploit the out-of-order packets. Finally, the experimental results show the advantage of the proposed approach over other approaches.

A Multi-Core Architecture for Video Streaming

In this paper, we focused on the architecture of video streaming based on multi-core processor. Compared with traditional video streaming server, multi-core architecture has a number of advantages: (1) according to system requirements, its flexible to add or remove executing core, (2) modules or units which consume much CPU resources can be configured to run concurrently on several cores, (3) multi-core architecture is fault-tolerant, and (4) the multi-core architecture fits well to future process technologies, more cores will be available in advanced process technologies, meanwhile the complexity per core does not increase. In order to improve the efficiency of video streaming and promote the concurrence number of tasks, we proposed a pipeline-parallel hybrid multi-core architecture on multi-core processor. We implemented the video streaming system with proposed architecture, and provided evidences of 48% outperformance based on Cavium OCTEON CN5860 multi-core processor than full parallel architecture.

Efficiency of Dynamic GOP Length in Video Stream

Multiple description codes are designed for multiple path video streaming with channel diversities and an efficient MDC technique based on the applied spatial domain processing features. In this paper, we investigate the performance of multi-path video streaming using a multiple description coding (MDC) technique, especially the impacts of several codec variables, such as different lengths of the Group of Pictures (GOP), and the different startup times of I-frame in each independent MDC sub-streams. The overall performance of the system is evaluated by the frame dropout rate, which indicates the probability of playing back frozen frames of the reconstructed video at the receiver devices. To address dynamic channel conditions for video transmissions, we propose an adaptive coding technique by adjusting the GOP lengths according to the channel condition and combinatorial mathematics optimization in length of GOP adjustment. Different approaches, such as sub-dividing GOPs for a single stream and multiple sub-streams, and an adaptive MDC video streaming system, are examined in this paper.

균일 화질 보장을 위한 스트리밍 비디오 시스템 설계에 관한 연구

스트리밍 비디오 시스템(SVS)의 QoS에 관한 기존 연구는 네트워크 관점에서 전송되는 비디오 스트림을 조절하여 데이터의 손실과 지연을 방지하는데 중점을 두고 있다. 반면 비디오 스트림의 화질이 변화되면 균일화질을 원하는 사용자 입장에서의 QoS는 보장 받지 못하는 것이다. 이러한 문제를 해결하기 위하여 본 논문에서는 Encoder에서 프레임 당 발생 비트량이 일정하게 유지되는 CBR 스트리밍 비디오의 장점과 균일한 화질을 보장하는 VBR 스트리밍 비디오의 장점을 적용한 VBR to CBR Encoder와 CBR to VBR Decoder, 비디오 스트림에 대한 재생 제어를 설계하였다. 그리고 이를 기반으로 사용자에게 균일한 화질의 제공을 보장하는 균일 화질 보장 SVS를 설계하고 구현하였다. 본 논문에서 제안한 균일 화질 보장 SVS의 우수성을 입증하기 위하여 여러 특성의 샘플 비디오에 대한 PSNR을 평가하였다. 평가결과 균일 화질 보장 SVS의 성능이 CBW가 ABR 100%부터 85%까지의 환경에서 균일한 화질을 보장하여 우수성을 입증하였다. The existing research on the QoS of the Streaming video system(SVS) adjust the video stream being sent from the network perspective, the focus is to prevent data loss and delay. The other hand, changing the quality of the video stream will not receive the guaranteed QoS from the perspective of the users who want uniform quality. In order to solve these problems, this paper applied to ensure that the benefits in the amount of bits per frame occurs Encoder CBR streaming video is kept constant and uniform picture quality advantages of VBR streaming video VBR to CBR Encoder and CBR to VBR Decoder, Video was designed to control the playback stream for And to ensure a uniform quality of the user based on the design and implementation of uniform quality guaranteed SVS. PSNR evaluated for several characteristics of the sample video to demonstrate the superiority of the SVS ensure uniform quality, the proposed Performance evaluation of the SVS ensure uniform quality CBW the ABR from 100% to ensure uniform image quality from 85% to environmental excellence is proved.

Real-time panoramic video streaming system with overlaid interface concept for social media

In this paper, we propose a real-time panoramic video streaming system with overlaid interface concept for social media. The proposed system provides real-time panorama images for smart displays such as smart TVs, smart phones, and tablet PCs. Panorama images are collected at sporting events via panorama cameras. Contents thus collected are sent to servers and then provided to smart devices via live sports video streams. Users select a panorama camera and choose their viewing angle and zooming factor for the selected panorama camera. The proposed system provides immersive and realistic views of live sporting events on users' displays. Furthermore, an overlaid panoramic interface concept is proposed for immersive live baseball watching combined with tightly integrated social media experience.

A scalable delivery solution and a pricing model for commercial video-on-demand systems with video advertisements

This paper presents a scalable delivery solution for commercial near on-demand video streaming systems with an associated pricing model. The proposed delivery solution combines the benefits of periodic broadcasting and stream merging, thereby enabling scalable video delivery. Video advertisements are delivered to the clients prior to viewing the requested videos. The revenues generated from the ads are used to subsidize the price of the requested videos. The pricing is determined based on the total ad viewing time. The proposed solution includes an efficient ad allocation scheme and a new constraint-based scheduling approach. In addition, the paper investigates how targeted advertisements can be efficiently supported. Furthermore, we investigate the effectiveness of the overall solutions and analyze and compare the effectiveness of various scheduling policies and ad allocation alternatives in terms of several metrics, including client defection probability, average number of viewed ads per client, price, channel utilization, revenue, and profit.

MATIN: A Random Network Coding Based Framework for High Quality Peer-to-Peer Live Video Streaming

In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.

A Decision Theoretic Approach for In-service QoE Estimation and Prediction of P2P Live Video Streaming Systems Based on User Behavior Modeling and Context Awareness

Peer-to-Peer (P2P) systems are fast becoming the most popular live video streaming solutions due to their self-scaling properties, ease of deployment, cost effective nature, content addition and content distribution properties. In order to improve the user related and network related quality of these systems, in-service QoE estimation and prediction is required. In this paper, in-service QoE is estimated and predicted based on decision theoretic approach by modeling the problem as a decision network. The results of this new improved approach for QoE estimation and prediction for P2P live video streaming systems shows that the estimated QoE is not only user-centric and context aware but also dynamic in nature as it changes with the changing situation. The proposed approach calculates the QoE quantitatively and as the results indicate can replaced the existing objective and hybrid QoE estimation approaches.

PileCast: Multiple bit rate live video streaming over BitTorrent

In recent years, the demand for live video streaming has steadily increased. Unfortunately, current video streaming architectures embody a number of drawbacks, which impact the quality of live video streaming and place a heavy demand on the video streaming server. Client–server architectures engender issues of network congestion, server bottlenecks and load-balancing, often leading to poor quality video playback at the client and thus making them inappropriate for live video streaming. Moreover, most live video streaming systems offer only a single, fixed bit rate video stream, which is typically not appropriate for all clients. If this bit rate is too high, then some clients may not possess sufficient bandwidth to view the video stream. Conversely, if it is set too low, then all clients will receive a low quality video stream, even those whose bandwidth can support a higher standard. The aforementioned issues can be addressed using multiple bit rate video streaming, thereby allowing clients to download content at a rate appropriate for their bandwidth. This paper focuses on the utilization of a BitTorrent-based, Peer-to-Peer (P2P) architecture, which mitigates the load on the video streaming server whilst supporting multiple bit rate live video streaming. Using this architecture, each client is able to share the responsibility of the streaming server by providing part of the steamed video content to other clients. Simulations conducted indicate that the proposed architecture offers better performance than both: the client–server approach and current P2P-based live video streaming systems.

Optimized MVC Prediction Structures for Interactive Multiview Video Streaming

The Multiview Video Coding (MVC) standard efficiently compresses multiview video by considering spatial, temporal and interview correlations. This letter studies the impact of the MVC interview prediction structure on both the transmission and the overall coding rates for an interactive multiview video streaming system, considering both unicast and multicast scenarios, with the user interactive behavior represented by some view-popularity model. We propose a method to identify the optimal prediction structure minimizing the visual distortion, given some storage and link capacities constraints. Simulation results confirm that the optimal prediction structure results from a non-trivial tradeoff between the system constraints, the transmission model and the views' popularity.

Quality of experience for 3D video streaming

New 3D video applications and services are emerging to fulfill increasing user demand. This effort is well supported by the increasing 3D video content including user generated content (e.g., through 3D capture/display enabled mobile phones), technological advancements (e.g., HD 3D video capture and processing methods), affordable 3D displays, and standardization activities. However, not much attention has been given to how these technologies, along the end-to-end chain from content capture to display, affect user perception and whether the overall experience of 3D video users is satisfactory or not. 3D video streaming also introduces artifacts on the reconstructed 3D video at the receiver end, leading to inferior quality and user experience. In this article we present and discuss in detail how artifacts introduced during 3D video streaming affect the end-user perception and how we could use realtime quality evaluation methodologies to overcome these effects. The observations presented can underpin the design of future QoE-aware 3D video streaming systems.

Development and benchmarking of HTTP-based multivision video server using fast stream joiner

High functionality and interactivity of video services are strongly desired. Earlier reports have presented an encoding scheme and a fast joining scheme for interactive multivision video streaming systems. Together, they enable numerous users to access any view area interactively at any desired resolution. The joining means the combination of multiple streams into a single video stream. The server joins pre-encoded multiple streams into one bitstream according to a user request; then the server transmits it simultaneously to many clients. This structure obviates complexity at the client terminal because the client terminal simply receives and decodes the single stream. This paper describes implementation of an actual HTTP-based streaming server by embedding the stream joiner module into a widely available HTTP server. The contribution of this paper is that the joining speed of the server surpasses the necessary speed attained with practical network equipment connecting to the server. Results of experiments described in this paper underscore the proposed method's effectiveness.

Dynamic Control of Receiver Buffers in Mobile Video Streaming Systems

We propose a novel algorithm to efficiently transmit multiple Variable-Bit-Rate (VBR) video streams from a base station to mobile receivers in wide-area wireless networks. The algorithm multicasts video streams in bursts to save the energy of mobile devices. In addition, the algorithm adaptively controls the buffer levels of mobile devices receiving different video streams according to the bit rate of the video stream being received by each device. Compared to previous algorithms, the new algorithm enables dynamic control of the wireless channel and allows the base station to transmit more video data on time to mobile receivers. This is done by providing finer control over the bandwidth allocation of the wireless channel. The problem of optimizing energy saving has been shown to be NP-Complete. We prove that our algorithm finds a feasible schedule if one exists and always produces a correct schedule even when dropped frames are unavoidable. We analytically bound the gap between the energy saving resulting from our algorithm and the optimal energy saving and show that our results are close to optimal. We analyze the tradeoff between the fine control over bandwidth allocation and energy saving and demonstrate that in practical situations, flexible and finer control of bandwidth allocation will result in significantly lower frame loss rates while achieving higher energy saving. We have implemented the proposed algorithm as well as two other recent algorithms in a mobile video streaming testbed. Our extensive analysis and results demonstrate that the proposed algorithm outperforms the other two algorithms; it results in higher energy saving for mobile devices and fewer dropped video frames.