视频流传输中的网络编码综述

网络视频应用增长迅猛,利用网络编码（NC）来提高网络吞吐量和传输可靠性进而改善视频流传输质量成为研究热点。针对如何优化网络编码进行视频流传输这一问题,必须要结合视频流自身特性作出改进并综合考虑所处的网络环境,才能充分发挥网络编码的优势。首先回顾了网络编码的基本概念和方法;然后对网络编码应用于视频流传输时需要考虑的视频业务特性,包括进行不等差错保护以优先保障重要等级视频数据包、降低数据包传输延迟以满足视频流实时性需求、增强网络差错恢复策略以提升传输可靠性等作了分析和归纳;接着阐述了基于网络编码的视频流传输策略在包括P2P、多源协作及内容中心网络等典型场景中的应用;最后对网络编码应用于视频流传输的研究趋势进行展望。     

Seamless switching of scalable video bitstreams for efficient streaming

Efficient adaptation to channel bandwidth is broadly required for effective streaming video over the Internet. To address this requirement, a novel seamless switching scheme among scalable video bitstreams is proposed in this paper. It can significantly improve the performance of video streaming over a broad range of bit rates by fully taking advantage of both the high coding efficiency of nonscalable bitstreams and the flexibility of scalable bitstreams, where small channel bandwidth fluctuations are accommodated by the scalability of a single scalable bitstream, whereas large channel bandwidth fluctuations are tolerated by flexible switching between different scalable bitstreams. Two main techniques for switching between video bitstreams are proposed. Firstly, a novel coding scheme is proposed to enable drift-free switching at any frame from the current scalable bitstream to one operated at lower rates without sending any overhead bits. Secondly, a switching-frame coding scheme is proposed to greatly reduce the number of extra bits needed for switching from the current scalable bitstream to one operated at higher rates. Compared with existing approaches, such as switching between nonscalable bitstreams and streaming with a single scalable bitstream, our experimental results clearly show that the proposed scheme brings higher efficiency and more flexibility in video streaming.     

Optimal proxy cache allocation for efficient streaming media distribution

We address the problem of efficiently streaming a set of heterogeneous videos from a remote server through a proxy to multiple asynchronous clients so that they can experience playback with low startup delays. We determine the optimal proxy prefix cache allocation to the videos that minimizes the aggregate network bandwidth cost. We integrate proxy caching with traditional server-based reactive transmission schemes such as hatching, patching and stream merging to develop a set of proxy-assisted delivery schemes. We quantitatively explore the impact of the choice of transmission scheme, cache allocation policy, proxy cache size, and availability of unicast versus multicast capability, on the resulting transmission cost. Our evaluations show that even a relatively small prefix cache (10%-20% of the video repository) is sufficient to realize substantial savings in transmission cost. We find that carefully designed proxy-assisted reactive transmission schemes can produce significant cost savings even in a predominantly unicast environment such as the Internet.     

Content-aware optimization on rate-distortion and network traffic for scalable video multicast networks

This paper aims to optimize the content-aware prioritization of scalable video multicast, which is coupled with multipath streaming and network coding based routing. It constructs multiple layer distribution meshes for the scalable video stream to minimize the total video distortion at all the receivers, determines the base layer meshes with minimum costs to maintain application-layer QoS and the layer synchronization of SVC streaming, and improves the network throughput by encouraging path-overlapping transmissions and thus allowing bandwidth sharing among different receivers for the same video layer by utilizing network coding. The targeted problem is formulated into a minimization programming in which the quality variation between layers, the transmission cost of the base layer, as well as the efficient resource utilization are jointly considered. By decomposition and dual approach, the global convex problem is solved by a two-level decentralized iterative algorithm. The implementation of the distributed algorithm is discussed with regard to the communication overhead, and the convergence performance is validated by numerical experiments. Packet-level simulations demonstrate that the proposed algorithm could approximately achieve the maximum flow rates determined by Max-Flow Min-Cut Theorem and benefit the overall received video quality.     

Parallel video streaming optimizing network throughput

In the Internet, video streaming services, in which users can enjoy videos at home, are becoming popular. Video streaming with high definition TV (HDTV) or ultra high definition video (UHDV) quality will be also provided and widely demanded in the future. However, the transmission bit-rate of high-quality video streaming is quite large, so generated traffic flows will cause link congestion. In the Internet, routes that packets take are determined using static link weights, so the network productivity, i.e., the maximum achievable throughout by the network, is determined by the capacity of a bottleneck link with the maximum utilization, although utilizations of many links remain low level. Therefore, when providing streaming services of rich content, i.e., videos with HDTV or UHDV quality, it is important to flatten the link utilization, i.e., reduce the maximum link utilization. We propose that ISPs use multiple servers to deliver rich content to balance the link utilization and propose server allocation and server selection methods for parallel delivery. We evaluate the effect of parallel delivery using 23 actual commercial ISP networks.     

Pyramid coding based rate control for constant bit rate video streaming

In this paper, a novel pyramid coding based rate control scheme is proposed for video streaming applications constrained by a constant channel bandwidth. To achieve the target bit rate with the best quality, the initial quantization parameter (QP) is determined by the average spatio-temporal complexity of the sequence, its resolution and the target bit rate. Simple linear estimation models are then used to predict the number of bits that would be necessary to encode a frame for a given complexity and QP. The experimental results demonstrate that the proposed rate control scheme significantly outperforms the existing rate control scheme in the Joint Model (JM) reference software in terms of Peak Signal to Noise Ratio (PSNR) and consistent perceptual visual quality while achieving the target bit rate. Finally, the proposed scheme is validated through experimental evaluation over a miniature test-bed.

     

A speculative load adaptive streaming scheme for efficient video delivery

Video on demand services require video broadcast schemes to provide efficient and reliable performance under various client request loads. In this paper, we have developed an efficient request load adaptive broadcast scheme, speculative load adaptive streaming scheme (SLAS), that requires lower service bandwidth than previous approaches, regardless of request rate. We have provided both analysis and simulation to show the performance gain over previous schemes. In this paper, we provide the theoretic upper bound of the continuous segment allocations on channels. We found that the number of allocated segments of the SLAS is close to the theoretic upper bound when compared with other schemes over various numbers of stream channels. Our analysis of client waiting time is almost identical to simulation results about all client requests. By simulation, we compared the required service bandwidth and storage requirements of the SLAS scheme and other schemes and found the SLAS scheme is an efficient broadcast scheme as compared to well known seamless channel transition schemes.     

Battery-aware rate adaptation for extending video streaming playback time

Multimedia streaming applications are computation and network intensive that put a high demand on battery usage of mobile devices. Battery usage forms an important metric in user satisfaction, as increased battery consumption results in faster battery depletion and eventually leads to battery outage. In this paper, we propose an adaptation technique, referred as Battery-Aware Rate Adaptation (BARA) scheme, which adapts to the appropriate bit rate to prolong the battery lifetime. BARA considers both the wireless channel conditions, as well as the device’s battery level, to determine the best transmission rate for optimizing the mobile battery consumption. Actual experiment and simulation results corroborate that compared to the conventional techniques, BARA can save more than 40% of battery power, while extending the video playback time by 20%.

     

A novel resource allocation mechanism for live cloud-based video streaming service

With the recent emergence of cloud computing, growing numbers of clients are using online cloud services through the Internet such as video streaming service. The rent costs of cloud service providers increase when the resource utilizations of the cloud-servers are not well. Therefore, resource allocation is a crucial problem for cloud data centers. The resource allocation problem is an NP-hard problem. This paper proposes a novel cloud resource allocation mechanism based on a winning strategy for a Nim game. This mechanism offers all clients an effective number of running cloud servers, and allocates cloud resources rapidly and effectively by using a pre-pairing approach. The proposed mechanism does not require searching for remaining resources of the running cloud server; hence, it can reduce the time taken to arrange resources. The experimental results show that the proposed mechanism can improve utilization of cloud servers and reduce the rent costs of the cloud service providers. The proposed mechanism can reach the utilization of cloud servers by as much as 99.96 %. The proposed mechanism is approximately 9 % more efficient than the market-based grid resource allocation algorithm, and 19 % more efficient than the modified best fit decreasing algorithm.

     

A systematic rate controller for MPEG-4 FGS video streaming

This paper proposes a systematic rate controller (SRC) for content-aware streaming of MPEG-4 FGS video over the Internet. An active layer dropping technique is proposed to provide both coarse-grain and fine-granularity scalability of smooth quality adaptation to bandwidth fluctuations and bit-rate variations of streamed video over a general time-scale. The smooth quality adaptation is realized through the mode and state transition of a state machine that implements the SRC. The SRC effectively uses available bandwidth and client buffer by forward-shifting the FGS video stream. It provides protection to video segments with important content by introducing a content-aware priority-based layer model for the MPEG-4 FGS video stream. RID="*" ID="*" The work reported in this paper was performed when this author was working at Microsoft Research Asia as a research intern.     

FJND-based fuzzy rate control of scalable video for streaming applications

Multimedia Tools and Applications - A fuzzy rate controller with buffer constraint in combination with a perceptual quality controller is proposed for streaming applications of the AVC/H.264...     

Towards efficient video chunk dissemination in peer-to-peer live streaming

There are substantial differences in chunk dissemination manner between P2P live streaming and BitTorrent, and inappropriate algorithms will result in inefficiency of live streaming systems. In this paper, we study the chunk dissemination of P2P live streaming, and introduce a discrete and slotted mathematical model to analyze chunk selection algorithms, including rarest first algorithm and greedy algorithm. Moreover, we present a performance metric to evaluate chunk selection algorithms, as well as the optimization function for the exploration of chunk dissemination strategies. We point out the causes of poor performance of these algorithms, and propose a service request randomization mechanism to promote the use of peer resources, which can prevent chunk requests from rendezvous on a few of peers. Simultaneously, we employ weight assignment strategies to avoid excessive requests for rare chunks. Besides, we present an enhanced model, which adds node degree constraint, to improve our model. We revisit the chunk selection algorithms based on the enhanced model. The results of simulation experiments validate our theoretical analysis and indicate that the weighted randomization mechanism is resilient to flash crowd and peer churn, and can improve the performance of P2P live streaming.     

Energy optimization for mobile video streaming via an aggregate model

Wireless video streaming on smartphones drains a significantly large fraction of battery energy, which is primarily consumed by wireless network interfaces for downloading unused data and repeatedly switching radio interface. In this paper, we propose an energy-efficient download scheduling algorithm for video streaming based on an aggregate model that utilizes user’s video viewing history to predict user behavior when watching a new video, thereby minimizing wasted energy when streaming over wireless network interfaces. The aggregate model is constructed by a personal retention model with users’ personal viewing history and the audience retention on crowd-sourced viewing history, which can accurately predict the user behavior of watching videos by balancing “user interest” and “video attractiveness”. We evaluate different users streaming multiple videos in various wireless environments and the results illustrate that the aggregate model can help reduce energy waste by 20 % on average. In addition, we also discuss implementation details and extensions, such as dynamically updating personal retention, balancing audience and personal retention, categorizing videos for accurate model.     

On dynamic memory allocation in sliding-window parallel patterns for streaming analytics

This work studies the issues related to dynamic memory management in Data Stream Processing, an emerging paradigm enabling the real-time processing of live data streams. In this paper, we consider two streaming parallel patterns and we discuss different implementation variants related to how dynamic memory is managed. The results show that the standard mechanisms provided by modern C++ are not entirely adequate for maximizing the performance. Instead, the combined use of an efficient general purpose memory allocator, a custom allocator optimized for the pattern considered and a custom variant of the C++ shared pointer mechanism, provides a performance improvement up to 16% on the best case.

     

Queueing network analysis on dynamic lot streaming

Lot streaming is a technique used to split a production lot into several smaller transfer batches. In this way, processing a product in a multistage serial production system by overlapping production between stages is available. As a result, production can be accelerated. In this paper, a modified N-policyM/G/1$N\text{-}\mathrm{policy}M/G/1$ queueing system with a non-reliable server is proposed. With the relevant parameters of this queueing system, the problem of lot streaming in dynamic situations can be solved. To obtain the optimal transfer batch size, a cost objective function including transport cost, repair cost, turning cost, and holding cost is formulated. Further, in order to illustrate the usefulness of the proposed methods, numerical examples are solved. On the basis of the results of these examples, some important conclusions are drawn.     

An efficient Nash-implementation mechanism for network resource allocation

We propose a mechanism for auctioning bundles of multiple divisible goods in a network where buyers want the same amount of bandwidth on each link in their route. Buyers can specify multiple routes (corresponding to a source-destination pair). The total flow can then be split among these multiple routes. We first propose a one-sided VCG-type mechanism. Players do not report a full valuation function but only a two-dimensional bid signal: the maximum quantity that they want and the per-unit price they are willing to pay. The proposed mechanism is a weak Nash implementation, i.e., it has a non-unique Nash equilibrium that implements the social-welfare maximizing allocation. We show the existence of an efficient Nash equilibrium in the corresponding auction game, though there may exist other Nash equilibria that are not efficient. We then generalize this to arbitrary bundles of various goods. Each buyer submits a bid separately for each good but their utility function is a general function of allocations of bundles of various divisible goods. We then present a double-sided auction mechanism for multiple divisible goods. We show that there exists a Nash equilibrium of this auction game which yields the efficient allocation with strong budget balance.     

基于资源效用最大化的虚拟网络功能备份方法

针对网络功能虚拟化环境下组成服务功能链的虚拟网络功能故障所引起的网络服务故障问题,提出一种最大化资源效用的虚拟服务功能备份方法来提高网络可靠性。首先,对虚拟服务功能备份问题进行详细分析并建立了可靠性评估模型,提出了改进的备份机制,并证明了该机制与其他机制相比的优势;其次,对全网络设计了全局备份算法和备份选择策略来对相应的虚拟网络功能选取备份直到满足可靠性需求。仿真实验结果表明,与GREP方法、联合备份机制加上随机选择策略（JP+random selection）及双重共享式备份机制加上随机选择策略（DSP+random selection）相比,该方法在可靠性和资源利用率上取得了优异的性能,特别是服务功能链请求接受率提高18.8%~25%,资源效用利用率提高15%~20%。实验结果表明该方法能较为有效地利用资源来提升网络可靠性。     

Performance of HTTP video streaming under different network conditions

Multimedia Tools and Applications - The Internet video sharing services have been gaining importance and increasing their share in the multimedia market. In order to compete effectively and provide...     

An efficient scheduling algorithm for scalable video streaming over P2P networks

During recent years, the Internet has witnessed rapid advancement in peer-to-peer (P2P) media streaming. In these applications, an important issue has been the block scheduling problem, which deals with how each node requests the media data blocks from its neighbors. In most streaming systems, peers are likely to have heterogeneous upload/download bandwidths, leading to the fact that different peers probably perceive different streaming quality. Layered (or scalable) streaming in P2P networks has recently been proposed to address the heterogeneity of the network environment. In this paper, we propose a novel block scheduling scheme that is aimed to address the P2P layered video streaming. We define a soft priority function for each block to be requested by a node in accordance with the block’s significance for video playback. The priority function is unique in that it strikes good balance between different factors, which makes the priority of a block well represent the relative importance of the block over a wide variation of block size between different layers. The block scheduling problem is then transformed to an optimization problem that maximizes the priority sum of the delivered video blocks. We develop both centralized and distributed scheduling algorithms for the problem. Simulation of two popular scalability types has been conducted to evaluate the performance of the algorithms. The simulation results show that the proposed algorithm is effective in terms of bandwidth utilization and video quality.     

Optimize adaptive media playout using dynamic fuzzy logic control for video streaming

Multimedia Tools and Applications - Adaptive Media Playout (AMP) controls adapt playout rate to prevent buffer outage and to reduce delay in playout. Most AMP techniques use buffer fullness or its...