No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
SVC-DASH-M: Scalable video coding dynamic adaptive streaming over HTTP using multiple connections
Abstract
Dynamic adaptive streaming over HTTP (DASH) has gained a significant momentum for multimedia streaming due to its ability in crossing firewalls and availability of infrastructure. In the mean time scalable video coding (SVC) is building a similar momentum as it enables efficient media storage and caching. In this work, we identify the main components of adaptive SVC-DASH client and propose an streaming heuristic over dynamic multiple connections. The proposed algorithm is experimentally tested under different connection and link configurations. Our results show that the algorithm successfully achieves interruption free streaming under all the tested bandwidth and link configurations. Additionally, the usage of multiple connections results in noticeable improvements in the achieved streaming quality for large link delays.
... They accommodate the variations in the transmission BW in order to avoid annoying streaming interruption [10,11]. Another problem of using HTTP streaming is the possibility of reducing the link efficiency due to Transmission Control Protocol (TCP) dynamics, however, this can be compensated by using a client-buffer [12]. ...
... In [5], it is shown that SVC-DASH has several advantages including the possibility of serving a larger number of users with different equipment capabilities and a higher caching efficiency. In [12], SVC-DASH not only needs less buffering requirements in comparison to AVC-DASH but it also improves the Quality of Experience (QoE) for the viewer. In [10], the authors compare the performance of different AVC-based and SVC-based heuristics using NS3 simulations with NS3 cradle. ...
Dynamic Adaptive Streaming over Hypertext Transfer Protocol HTTP (DASH) has gained a significant momentum for multimedia streaming due to its ability in crossing firewalls and availability of infrastructure. In the mean time, Scalable Video Coding (SVC) is building a similar momentum as it enables efficient media storage and caching. In this work, we identify the main components of adaptive SVC-DASH client and propose a streaming heuristic over dynamic multiple connections. The proposed algorithm is experimentally tested under different connection and link configurations. Our results show that the algorithm successfully achieves interruption free streaming under all the tested BandWidth and link configurations. Additionally, the usage of multiple connections results in noticeable improvements in the achieved streaming quality for large link delays. © 2018 International Journal of Computing and Digital Systems. All rights reserved.
... SVC-DASH-M [28] is an SVC-based HAS system that uses multiple networks. This uses several parameters related to the QoE factor to determine the quality of the segment. ...
HTTP adaptive streaming (HAS) is a state-of-the-art technology for video streaming. Optimal adaptive streaming schemes should be designed to maximize the quality of experience (QoE) in network environments with unstable bandwidths such as wireless networks. QoE is degraded for Advanced Video Coding (AVC)-based HAS due to frequent quality switching and rebuffering in wireless networks. Meanwhile, Scalable Video Coding (SVC)-based HAS can maximize the QoE by flexibly requesting the base layer (BL) and enhancement layer (EL) based on variable network conditions. However, in SVC-based HAS, the required bandwidth is significantly high due to the encoding overhead. In this paper, we propose a layer-assisted video quality adaptation for improving QoE in wireless networks. The proposed scheme employs a video encoding method, composed of multiple BLs and ELs, using both AVC and SVC. The quality of the BL is determined using the buffer occupancy level and measured bandwidth to minimize rebuffering. The quality of the EL is determined using the buffer region and segment quality differences to minimize instability. enhancement dummy (ED) consists of the selected ELs. The layer scheduler decides the segment that is to be requested based on the QoE model according to the BL and ED to maximize the QoE. Experimental results show that the proposed scheme achieves high QoE compared to the existing schemes because the instability is low and no rebuffering occurs.
... More complex encoding scenarios, exploiting the inter-view redundancy by using scalable video coding, have been successfully used to create adaptation sets for adaptive streaming of perspective videos [17,20,33], even in the case of multi-view perspective videos, as discussed in Section 2. While such scalable encoding solutions could be suitable for the MVP 360°scenario, eventually in combination with tiling, these options are out of the scope of this paper: we only consider encoding scenarios that do not use scalability. ...
Full immersion inside a Virtual Reality (VR) scene requires six Degrees of Freedom (6DoF) applications where the user is allowed to perform translational and rotational movements within the virtual space. The implementation of 6DoF applications is however still an open question. In this paper we study a multi-viewpoint (MVP) 360-degree video streaming system, where a scene is simultaneously captured by multiple omnidirectional video cameras. The user can only switch positions to predefined viewpoints (VPs). We focus on the new challenges that are introduced by adaptive MVP 360-degree video streaming. We introduce several options for video encoding with existing technologies, such as High Efficiency Video Coding (HEVC) and for the implementation of VP switching. We model three video-segment download strategies for an adaptive streaming client into Mixed Integer Linear Programming (MILP) problems: an omniscient download scheduler; one where the client proactively downloads all VPs to guarantee fast VP switch; one where the client reacts to the user's navigation pattern. We recorded a one MVP 360-degree video with three VPs, implemented a mobile MVP 360-degree video player, and recorded the viewing patterns of multiple users navigating the content. We solved the adaptive streaming optimization problems on this video considering the collected navigation traces. The results emphasize the gains obtained by using tiles in terms of objective quality of the delivered content. They also emphasize the importance of performing further study on VP switching prediction to reduce the bandwidth consumption and to measure the impact of VP switching delay on the subjective Quality of Experience (QoE).
... For instance, the effectiveness of using SVC content for DASH video streaming in analyzed in [3,4]. Ibrahim et al. [5] show how it is possible to optimize the performance of DASH streaming of SVC content on high-delay links by using multiple TCP connections. For mobile video uploading Seo et al. [6] present a system that can send video from a mobile device to a server that performs transcoding and adaptation for redistribution using DASH. ...
This work addresses the increasingly common case of a user who wants to record a video with a mobile device and share it in (near) real-time with other users in the Internet using HTTP streaming. The proposed system builds on scalable video coding (SVC) to provide some degrees of adaptation to the users watching the video without the support of a costly high-performance low-latency video transcoding server. At the same time, the DASH standard is used to leverage the scalable video for providing HTTP streaming adaptation to users watching the video. The performance of several chunk uploading strategies are investigated by simulations, evaluating the tradeoff between several parameters such as video quality, buffering rate, idle time, and the startup delay of the clients. Finally, experimental results on a testbed confirm the simulation results.
... A video bit stream is called scalable if a part of the stream can be removed in such a way that the resulting bit stream is still decodable. The three types of scalability are [16]: ...
With the fast progress of wireless networks bandwidth and mobile devices, large scale digital video library systems are growing rapidly. However, the huge increasing of content and the data intensive nature of video make the management and browsing of video collections, as well as their search and retrieval, increasingly difficult.
The need of having a media digital library is essential these days with intelligent tools for indexing the video with allocating the suitable metadata that describe the content of such videos and appropriate tools for retrieving the archived video with fast techniques. These will be achieved in 3 steps, working on the stream coding with multi bit rates and methods of handling, representing the video with summarized stream carrying the same information of the full stream and deriving a media digital library for indexing and retrieval process. The first step, stream handling, will address implementing scalable video techniques which set the bit rate according to the required application and the delivery devices. Scalable video coding offers a solution for meeting such heterogeneous requirements. The second step, video summarization, plays an important role in this context; it makes navigation easier and provides the user with a quick idea about the content. Another issue is that the same video content can be accessed from a wide variety of terminal devices which differ with respect to bandwidth limitation, decoding complexity, power constraints and screen size. The third step is implementing a media digital library for storing the code and/ or the summarized video based on Media Asset management system.
The main contribution of this paper is to explore the use of scalable video coding and video summarization techniques to enhancing a digital video library and the integration between these 3 modules.
This paper presents new techniques and mechanisms for carrying streams of layered video using Scalable Video Coding (SVC) from servers to clients, utilizing the Packet Wash mechanism which is part of the Big Packet Protocol (BPP). BPP was designed to handle the transfer of packets for high-bandwidth, low-latency applications, aiming to overcome a number of issues current networks have with high precision services. One of the most important advantages of BPP is that it allows the dynamic adaption of packets during transmission. BPP uses Packet Wash to reduce the payload, and the size of a packet by eliminating specific chunks. For video, this means cutting out specific segments of the transferred video, rather than dropping packets, as happens with UDP based transmission, or retrying the transmission of packets, as happens with TCP. The chunk elimination approach is well matched with SVC video, and these techniques and mechanisms are utilized and presented. An evaluation of the performance is provided, plus a comparison of using UDP or TCP, which are the other common approaches for carrying media over IP. Our main contributions are the mapping of SVC video into BPP packets to provide low latency, low loss delivery, which provides better QoE performance than either UDP or TCP, when using those techniques and mechanisms. This approach has proved to be an effective way to enhance the performance of video streaming applications, by obtaining continuous delivery, while maintaining guaranteed quality at the receiver. In this work we have successfully used an H264 SVC encoded video for layered video transmission utilizing BPP, and can demonstrate video delivery with low latency and low loss in limited bandwidth environments.
The extensive growth in smartphone and tablet market has led to a continuous increase in mobile video traffic, which has urged mobile network operators (MNOs) to redesign their networks and search for cost-effective solutions to bring content closer to the end-user. This enables support for more simultaneous video streams while maintaining stringent delay bounds. However, with adaptive bit rate streaming (ABS) which provides multiple source video bit rates for a single video to meet the heterogeneity of user devices and network conditions, caching all rate variants significantly increases backhaul and storage requirements. There- fore, having cached the highest quality of video contents, this thesis proposes two methodologies to perform in-network video adaptation: (1) a perceptual quality-aware video adaptation scheme that encodes video sequences at a target bit rate; (2) a quality of experience (QoE)-aware video adaptation technique which drops packets from scalable video streams to produce lower bit-rate versions under QoE and delay constraints. These adaptation schemes then allocate resources to meet the delay limitation of the lower rate streams for power-efficient streaming over downlink OFDMA systems.
Alternatively, instead of transrating reactively cached contents, operators can implement intelligent caching in their networks. Predictable user demands can then be proactively served from content caches deployed at mobile gateways in the vicinity of users. Therefore, this thesis also evaluates the potential benefits from in-network caching of scalable videos and finds the trade-off between the potential savings from- and infrastructural costs of in-network caching.
In light of the increasing trend in virtualization of network functions, a cost-effective Caching-as-a-Service (CaaS) framework for virtual video caching in 5G mobile networks is proposed in this study. In order to evaluate the pros and cons of this CaaS approach, a virtual caching problem is formulated in order to maximize return on caching investment by finding the best trade-off between the cost of cache storage and bandwidth savings from caching video contents in the MNO’s cloud.
In this paper, we propose a quality-level selection method for adaptive video streaming with scalable video coding (SVC). The proposed method works on the client with the dynamic adaptive streaming over HTTP (DASH) with SVC. The proposed method consists of two components: introducing segment group and a buffer-aware layer selection algorithm. In general, quality of experience (QoE) performance degrades due to stalling (playback buffer underflow), low playback quality, frequent quality-level switching, and extreme-down quality switching. The proposed algorithm focuses on reducing the frequent quality-level switching, and extreme-down quality switching without increasing stalling and degrading playback quality. In the proposed method, a SVC-DASH client selects a layer every G segments, called a segment group to prevent frequent quality-level switching. In addition, the proposed method selects the quality of a layer based on a playback buffer in a layer selection algorithm for preventing extreme-down switching. We implement the proposed method on a real SVC-DASH system and evaluate its performance by subjective evaluations of multiple users. As a result, we confirm that the proposed algorithm can obtain better mean opinion score (MOS) value than a conventional SVC-DASH, and confirmthat the proposed algorithm is effective to improve QoE performance in SVC-DASH.
Sharing live multimedia content is becoming increasingly popular among mobile users. In this article, we study the problem of optimizing video quality in such a scenario using scalable video coding (SVC) and chunked video content. We consider using only standard stateless HTTP servers that do not need to perform additional processing of the video content. Our key contribution is to provide close to optimal algorithms for scheduling video chunk upload for multiple clients having different viewing delays. Given such a set of clients, the problem is to decide which chunks to upload and in which order to upload them so that the quality-delay tradeoff can be optimally balanced. We show by means of simulations that the proposed algorithms can achieve notably better performance than naive solutions in practical cases. Especially the heuristic-based greedy algorithm is a good candidate for deployment on mobile devices because it is not computationally intensive but it still delivers in most cases on-par video quality compared to the more complex local optimization algorithm. We also show that using shorter video segments and being able to predict bandwidth and video chunk properties improve the delivered video quality in certain cases.
Owing to the increase in consumption of multimedia content and the improvement of device capacity, user demand for high-quality content has increased. However, it is difficult to transport such large amounts of content over the existing broadcasting network with limited bandwidth. To provide high-definition broadcasting, some studies suggest methods of transporting multimedia over heterogeneous networks after encoding content hierarchically. MPEG Media Transport (MMT), standardized by Moving Picture Experts Group (MPEG), is a solution that enables large-volume media transport over heterogeneous networks such as digital broadcasting networks and packet-switched networks. In the case of delivering a scalable encoded video over different networks, synchronization of each stream is an important issue. MMT defines a synchronization scheme, but does not contain sufficient functions to implement it. In this paper, we propose a synchronization scheme for media streams that are encoded hierarchically, divided into layers, and transported over heterogeneous networks. We implement our scheme using MMT and HTTP, and experimented using three encapsulated video streams with different durations. As a result, we show that the proposed scheme can reduce the waiting time to display high-quality video, relative to Dynamic Adaptive Streaming over HTTP-Scalable Video Coding (DASH-SVC) by requesting segments of enhanced layers after calculating the transmission time. Additionally, we find out that the selection of durations have a relation to the characteristics of the video.
HTTP Adaptive Streaming (HAS) is becoming the de-facto standard for Over-The-Top video streaming services. Video content is temporally split into segments which are offered at multiple qualities to the clients. These clients autonomously select the quality layer matching the current state of the network through a quality selection heuristic. Recently, academia and industry have begun evaluating the feasibility of adopting layered video coding for HAS. Instead of downloading one file for a certain quality level, scalable video streaming requires downloading several interdependent layers to obtain the same quality. This implies that the base layer is always downloaded and is available for playout, even when throughput fluctuates and enhancement layers can not be downloaded in time. This layered video approach can help in providing better service quality assurance for video streaming. However, adopting scalable video coding for HAS also leads to other issues, since requesting multiple files over HTTP leads to an increased impact of the end-to-end delay and thus on the service provided to the client. This is even worse in a Live TV scenario where the drift on the live signal should be minimized, requiring smaller segment and buffer sizes. In this paper, we characterize the impact of delay on several measurement-based heuristics. Furthermore, we propose several ways to overcome the end-to-end delay issues, such as parallel and pipelined downloading of segment layers, to provide a higher quality for the video service.
HTTP Adaptive Streaming (HAS) is quickly becoming the dominant type of video streaming in Over-The-Top multimedia services. HAS content is temporally segmented and each segment is offered in different video qualities to the client. It enables a video client to dynamically adapt the consumed video quality to match with the capabilities of the network and/or the client's device. As such, the use of HAS allows a service provider to offer video streaming over heterogeneous networks and to heterogeneous devices. Traditionally, the H.264/AVC video codec is used for encoding the HAS content: for each offered video quality, a separate AVC video file is encoded. Obviously, this leads to a considerable storage redundancy at the video server as each video is available in a multitude of qualities. The recent Scalable Video Codec (SVC) extension of H.264/AVC allows encoding a video into different quality layers: by dowloading one or more additional layers, the video quality can be improved. While this leads to an immediate reduction of required storage at the video server, the impact of using SVC-based HAS on the network and perceived quality by the user are less obvious. In this article, we characterize the performance of AVC- and SVC-based HAS in terms of perceived video quality, network load and client characteristics, with the goal of identifying advantages and disadvantages of both options.
In this paper, we provide some insight and background into the Dynamic Adaptive Streaming over HTTP (DASH) specifications as available from 3GPP and in draft version also from MPEG. Specifically, the 3GPP version provides a normative description of a Media Presentation, the formats of a Segment, and the delivery protocol. In addition, it adds an informative description on how a DASH Client may use the provided information to establish a streaming service for the user. The solution supports different service types (e.g., On-Demand, Live, Time-Shift Viewing), different features (e.g., adaptive bitrate switching, multiple language support, ad insertion, trick modes, DRM) and different deployment options. Design principles and examples are provided.
MPEG Dynamic Adaptive Streaming over HTTP (DASH) is a new streaming standard that has been recently ratified as an international standard (IS). In comparison to other streaming systems, e.g., HTTP progressive download, DASH is able to handle varying bandwidth conditions providing smooth streaming. Furthermore, it enables NAT and Firewall traversal, flexible and scalable deployment as well as reduced infrastructure costs due to the reuse of existing Internet infrastructure components, e.g., proxies, caches, and Content Distribution Networks (CDN). Recently, the Hypertext Transfer Protocol Bis (httpbis) working group of the IETF has officially started the development of HTTP 2.0. Initially three major proposals have been submitted to the IETF i.e., Googles' SPDY, Microsofts' HTTP Speed+Mobility and Network-Friendly HTTP Upgrade, but SPDY has been chosen as working draft for HTTP 2.0. In this paper we implemented MPEG-DASH over HTTP 2.0 (i.e., SPDY), demonstrating its potential benefits and drawbacks. Moreover, several experimental evaluations have been performed that compare HTTP 2.0 with HTTP 1.1 and HTTP 1.0 in the context of DASH. In particular, the protocol overhead, the performance for different round trip times, and DASH with HTTP 2.0 in a lab test scenario has been evaluated in detail.
Video streaming on the Internet is increasingly using Dynamic Adaptive Streaming over HTTP (DASH), which allows a client to dynamically adjust its video quality by choosing the appropriate quality level for each segment based on the current download rate. In this paper we examine the impact of Scalable Video Coding (SVC) on the client's quality selection policy. Given a variable download rate, when should the client try to maximize the current segment's video quality, and when should it instead play it safe and ensure a minimum level of quality for future segments? We use a combination of analysis, dynamic programming, and simulation to show that a client should use a diagonal quality selection policy, which combines prefetching with backfilling to balance both of these concerns. We also illustrate the conditions that affect the slope of the diagonal policy.
HTTP-based delivery for Video on Demand (VoD) has been gaining popularity within recent years. Progressive Download over HTTP, typically used in VoD, takes advantage of the widely deployed network caches to relieve video servers from sending the same content to a high number of users in the same access network. However, due to a sharp increase in the requests at peak hours or due to cross-traffic within the network, congestion may arise in the cache feeder link or access link respectively. Since the connection characteristics may vary over the time, with Dynamic Adaptive Streaming over HTTP (DASH), a technique that has been recently proposed, video clients may dynamically adapt the requested video quality for ongoing video flows, to match their current download rate as good as possible. In this work we show the benefits of using the Scalable Video Coding (SVC) for such a DASH environment.
With the introduction of the H.264/AVC video coding standard, significant improvements have recently been demonstrated in video compression capability. The Joint Video Team of the ITU-T VCEG and the ISO/IEC MPEG has now also standardized a Scalable Video Coding (SVC) extension of the H.264/AVC standard. SVC enables the transmission and decoding of partial bit streams to provide video services with lower temporal or spatial resolutions or reduced fidelity while retaining a reconstruction quality that is high relative to the rate of the partial bit streams. Hence, SVC provides functionalities such as graceful degradation in lossy transmission environments as well as bit rate, format, and power adaptation. These functionalities provide enhancements to transmission and storage applications. SVC has achieved significant improvements in coding efficiency with an increased degree of supported scalability relative to the scalable profiles of prior video coding standards. This paper provides an overview of the basic concepts for extending H.264/AVC towards SVC. Moreover, the basic tools for providing temporal, spatial, and quality scalability are described in detail and experimentally analyzed regarding their efficiency and complexity.
HTTP adaptive streaming (HAS) is rapidly evolving into a key video delivery technology, supported by implementations from Microsoft, Apple, and Adobe, and actively pursued by standardization organizations. Using segments in multiple video qualities, distributed via an already available Hypertext Transfer Protocol (HTTP) delivery infrastructure, a HAS client is able to seamlessly adapt to the available bandwidth in the network. However, existing HAS solutions have a number of disadvantages such as the additional storage and bandwidth requirements, a large playout buffer to absorb network impairments, and a non-optimal quality selection under fluctuating network conditions. In this paper, we investigate the opportunity of combining HAS with scalable video coding. We show that this combination creates possibilities to reduce the client buffer, which implies improvements for live and interactive video, and reduces storage requirements, increases the cache hit-ratio for supporting content delivery network (CDN) nodes, and demonstrates more robust behavior in the HAS client, ultimately improving the quality of experience (QoE) for the viewer.© 2012 Alcatel-Lucent. © 2012 Wiley Periodicals, Inc.
Recently the 3rd Generation Partnership Project (3GPP) and the Moving Picture Experts Group (MPEG) specified Dynamic Adaptive Streaming over HTTP (DASH) to cope with the shortages in progressive HTTP based downloading and Real-time Transport Protocol (RTP) over the User Datagram Protocol (UDP), shortly RTP/UDP, based streaming. This paper investigates rate adaptation for the serial segment fetching method and the parallel segment fetching method in Content Distribution Network (CDN). The serial segment fetching method requests and receives segments sequentially whereas the parallel segment fetching method requests media segments in parallel. First, a novel rate adaptation metric is presented in this paper, which is the ratio of the expected segment fetch time (ESFT) and the measured segment fetch time to detect network congestion and spare network capacity quickly. ESFT represents the optimum segment fetch time determined by the media segment duration multiplied by the number of parallel HTTP threads to deliver media segments and the remaining duration to fetch the next segment to keep a certain amount of media time in the client buffer. Second, two novel rate adaptation algorithms are proposed for the serial and the parallel segment fetching methods, respectively, based on the proposed rate adaptation metric. The proposed rate adaptation algorithms use a step-wise switch-up and a multi-step switch-down strategy upon detecting the spare networks capacity and congestion with the proposed rate adaptation metric. To provide a good convergence in the representation level for DASH in CDN, a sliding window is used to measure the latest multiple rate adaptation metrics to determine switch-up. To decide switch-down, a rate adaptation metric is used. Each rate adaptation metric represents a reception of a segment/portion of a segment, which can be fetched from the different edge servers in CDN, hence it can be used to estimate the corresponding edge server bandwidth. To avoid buffer overflow due to a slight mismatch in the optimum representation level and bandwidth, an idling method is used to idle a given duration before sending the next segment. In order to solve the fairness between different clients who compete for bandwidth, the prioritized optimum segment fetch time is assigned to the newly joined clients. The proposed rate adaptation method does not require any transport layer information, which is not available at the application layer without cross layer communication. Simulation results show that the proposed rate adaptation algorithms for the serial and the parallel segment fetching methods quickly adapt the media bitrate to match the end-to-end network capacity, provide an advanced convergence and fairness between different clients and also effectively control buffer underflow and overflow for DASH in CDN. The reported simulation results demonstrate that the parallel rate adaptation outperforms the serial DASH rate adaptation algorithm with respect to achievable media bitrates while the serial rate adaptation is superior to the parallel DASH with respect to the convergence and buffer underflow frequency.
In this paper, we propose an optimization algorithm called Intelligent Bitrate Switching-based Adaptive Video Streaming (ISAVS) to address the key issue of bitrate switching in HTTP-based adaptive video streaming. Our proposed solution can provide the best possible video quality to users with minimum replay interruption, which is reported as one of the key video quality issues of on-line video streaming over wireless access networks. While the optimization algorithm is based on IIS Smooth Streaming architecture [1], it can be easily applied by other proposed approaches, such as Adobe Flash Dynamic Streaming, and Apple HTTP Adaptive Bitrate Streaming. Simulations show that our optimization algorithm selects the best video bitrate according to channel condition and the amount of video stream buffered in the client to provide viewers the best possible quality while reducing the number of interruptions.