Dynamic Resource Allocation for MGS H.264/AVC Video Transmission Over Link-Adaptive Networks

In this paper, we address the problem of efficiently allocating network resources to support multiple scalable video streams over a constrained wireless channel. We present a resource allocation framework that jointly optimizes the operation of the link adaptation scheme in the physical layer (PHY), and that of a traffic control module in the network or medium access control (MAC) layer in multirate wireless networks, while satisfying bandwidth/capacity constraints. Multirate networks, such as IEEE 802.16 or IEEE 802.11, adjust the PHY coding and modulation schemes to maintain the reliability of transmission under varying channel conditions. Higher reliability is achieved at the cost of reduced PHY bit-rate which in turn necessitates a reduction in video stream bit-rates. The rate reduction for scalable video is implemented using a traffic control module. Conventional solutions operate unaware of the importance and loss tolerance of data and drop the higher layers of scalable video altogether. In this paper, we consider medium grain scalable (MGS) extension of H.264/AVC video and develop new rate and distortion models that characterize the coded bitstream. Performance evaluations show that our proposed framework results in significant gains over existing schemes in terms of average video PSNR that can reach 3 dB in some cases for different channel SNRs and different bandwidth budgets.      

Distributed Rate Allocation Policies for Multihomed Video Streaming Over Heterogeneous Access Networks

We consider the problem of rate allocation among multiple simultaneous video streams sharing multiple heterogeneous access networks. We develop and evaluate an analytical framework for optimal rate allocation based on observed available bit rate (ABR) and round-trip time (RTT) over each access network and video distortion-rate (DR) characteristics. The rate allocation is formulated as a convex optimization problem that minimizes the total expected distortion of all video streams. We present a distributed approximation of its solution and compare its performance against ${rm H}^{infty} $-optimal control and two heuristic schemes based on TCP-style additive-increase-multiplicative-decrease (AIMD) principles. The various rate allocation schemes are evaluated in simulations of multiple high-definition (HD) video streams sharing multiple access networks. Our results demonstrate that, in comparison with heuristic AIMD-based schemes, both media-aware allocation and ${rm H}^{infty} $-optimal control benefit from proactive congestion avoidance and reduce the average packet loss rate from 45% to below 2%. Improvement in average received video quality ranges between 1.5 to 10.7 dB in PSNR for various background traffic loads and video playout deadlines. Media-aware allocation further exploits its knowledge of the video DR characteristics to achieve a more balanced video quality among all streams.      

基于视频通信的信道码码率分配方法

针对差错信道下视频信源的不等差错保护问题,设计一个新的信道码码率分配策略,对一个图片组中不同位置的帧给予不同强度的保护。该策略考虑了视频信源的误码扩散问题,分析了差错掩盖方法与信道失真计算的关系,通过在编码端有效估计信道差错所引入的失真并建立最优码率分配问题,利用遗传算法快速得到最优的信道码码率分配方案。实验采用H.264视频编码标准,结果证明该策略能较好地提升视频传输系统性能。     

A study on visual sensor network cross-layer resource allocation using quality-based criteria and metaheuristic optimization algorithms

Visual sensor networks (VSNs) consist of spatially distributed video cameras that are capable of compressing and transmitting the video sequences they acquire. We consider a direct-sequence code division multiple access (DS-CDMA) VSN, where each node has its individual requirements in compression bit rate and energy consumption, depending on the corresponding application and the characteristics of the monitored scene. We study two optimization criteria for the optimal allocation of the source and channel coding rates, which assume discrete values, as well as for the power levels of all nodes, which are continuous, under transmission bit rate constraints. The first criterion minimizes the average distortion of the video received by all nodes, while the second one minimizes the maximum video distortion among all nodes. The resulting mixed integer optimization problems are tackled with a modern optimization algorithm, namely particle swarm optimization (PSO), as well as a hybrid scheme that combines PSO with the deterministic Active-Set optimization method. Extensive experimentation on interference-limited as well as noisy environments offers significant intuition regarding the effectiveness of the considered optimization schemes, indicating the impact of the video sequence characteristics on the joint determination of the transmission parameters of the VSN.     

Rate-distortion optimized distributed packet scheduling of multiple video streams over shared communication resources

We consider the problem of distributed packet selection and scheduling for multiple video streams sharing a communication channel. An optimization framework is proposed, which enables the multiple senders to coordinate their packet transmission schedules, such that the average quality over all video clients is maximized. The framework relies on rate-distortion information that is used to characterize a video packet. This information consists of two quantities: the size of the packet in bits, and its importance for the reconstruction quality of the corresponding stream. A distributed streaming strategy then allows for trading off rate and distortion, not only within a single video stream, but also across different streams. Each of the senders allocates to its own video packets a share of the available bandwidth on the channel in proportion to their importance. We evaluate the performance of the distributed packet scheduling algorithm for two canonical problems in streaming media, namely adaptation to available bandwidth and adaptation to packet loss through prioritized packet retransmissions. Simulation results demonstrate that, for the difficult case of scheduling nonscalably encoded video streams, our framework is very efficient in terms of video quality, both over all streams jointly and also over the individual videos. Compared to a conventional streaming system that does not consider the relative importance of the video packets, the gains in performance range up to 6 dB for the scenario of bandwidth adaptation, and even up to 10 dB for the scenario of random packet loss adaptation.     

Error-resilient surveillance video transmission based on a practical joint source-channel distortion computing model

In recent years, IP (Internet Protocol)-based video surveillance has widely been useful for post-event analysis and assisting the work of privacy protection and public safety. To support high-quality IP video surveillance, error-resilience techniques are important for surveillance system design, because video has more stringent requirements than general video transmission for packet loss, latency, and jitter. The optimal FEC (forward error correction) code rate decision is a crucial procedure to determine the optimal source and channel coding rates to minimize the overall picture distortion when transporting video packets over packet loss channels. The conventional FEC code rate decision schemes using an analytical source-coding distortion model and a channel-induced distortion model are usually complex and typically employ the process of model parameter training, which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate joint source-channel distortion model to estimate the channel-loss threshold set for optimal FEC code rate decision. Since the proposed model is expressed as a simple closed form and has a small number of scene-dependent model parameters, a video sender of the surveillance system using the model can be easily implemented. For training the scene-dependent model parameters in real time, we propose a practical test-run procedure. This method accelerates the test-run while maintaining its accuracy for training the scene-dependent model parameters. Using the proposed simple model and practical test-run method, the video sender can find the optimal code rate for on-the-fly joint source-channel coding whenever there is a change in the packet-loss condition in the channel. Simulations show that the proposed method can accurately estimate the channel loss threshold set, resulting in an optimal FEC code rate with low computational complexity.     

Low-Delay Low-Complexity Bandwidth-Constrained Wireless Video Transmission Using SVC Over MIMO Systems

We propose an efficient strategy for the transmission of scalable video over multiple-input multiple-output (MIMO) wireless systems. In this paper, we use the latest scalable H.264 codec (SVC), which provides combined temporal, quality and spatial scalability. At the transmitter, we estimate the decoded video distortion for given channel conditions taking into account the effects of quantization, packet loss and error concealment. The proposed scalable decoder distortion algorithm offers low delay and low complexity. The performance of this method is validated using experimental results. In our proposed system, we use a MIMO system with orthogonal space-time block codes (O-STBC) that provides spatial diversity and guarantees independent transmission of different symbols within the block code. The bandwidth constrained allocation problem considered here is simplified and solved for one O-STBC symbol at a time. Furthermore, we take the advantage of the hierarchical structure of SVC to attain the optimal solution for each group of pictures (GOP) of the video sequence. We incorporate the estimated decoder distortion to optimally select the application layer parameter, i.e., quantization parameter (QP), and physical layer parameters, i.e., channel coding rate and modulation type for wireless video transmission.      

Minimizing Resource Cost for Camera Stream Scheduling in Video Data Center

Video surveillance service, which receives live streams from IP cameras and forwards the streams to end users, has become one of the most popular services of video data center. The video data center focuses on minimizing the resource cost during resource provisioning for the service. However, little of the previous work comprehensively considers the bandwidth cost optimization of both upload and forwarding streams, and the capacity of the media server. In this paper, we propose an efficient resource scheduling approach for online multi-camera video forwarding, which tries to optimize the resource sharing of media servers and the networks together. Firstly, we not only provide a fine-grained resource usage model for media servers, but also evaluate the bandwidth cost of both upload and forwarding streams. Without loss of generality, we utilize two resource pricing models with different resource cost functions to evaluate the resource cost: the linear cost function and the non-linear cost functions. Then, we formulate the cost minimization problem as a constrained integer programming problem. For the linear resource cost function, the drift-plus-penalty optimization method is exploited in our approach. For non-linear resource cost functions, the approach employs a heuristic method to reduce both media server cost and bandwidth cost. The experimental results demonstrate that our approach obviously reduces the total resource costs on both media servers and networks simultaneously.     

Optimal Coding of Multilayer and Multiversion Video Streams

Traditional video servers partially cope with heterogeneous client populations by maintaining a few versions of the same stream with different bit rates. More recent video servers leverage multilayer scalable coding techniques to customize the quality for individual clients. In both cases, heuristic, error-prone, techniques are currently used by administrators to determine either the rate of each stream version, or the granularity and rate of each layer in a multilayer scalable stream. In this paper, we propose an algorithm to determine the optimal rate and encoding granularity of each layer in a scalable video stream that maximizes a system-defined utility function for a given client distribution. The proposed algorithm can be used to compute the optimal rates of multiversion streams as well. Our algorithm is general in the sense that it can employ arbitrary utility functions for clients. We implement our algorithm and verify its optimality, and we show how various structuring of scalable video streams affect the client utilities. To demonstrate the generality of our algorithm, we consider three utility functions in our experiments. These utility functions model various aspects of streaming systems, including the effective rate received by clients, the mismatch between client bandwidth and received stream rate, and the client-perceived quality in terms of PSNR. We compare our algorithm against a heuristic algorithm that has been used before in the literature, and we show that our algorithm outperforms it in all cases.     

一种基于MPEG-4视频编码流的信道失真模型

准确地估算信道失真是视频通信系统中联合功率率失真（P-R-D）优化的重要基础,提出了一种基于MPEG-4视频编码流的信道失真模型,采用帧间递归,根据信道平均误比特率和视频编码信息在编码器端实时估算视频序列的信道失真,仿真结果表明,对于不同的视频编码序列,在不同信道误比特率和信源编码率下,模型估算的平均相对偏差和绝对偏差较小,准确度高,为基于P-R-D优化的失真估算提供一个有力的工具。     

一种基于分层率失真优化的容错性视频转码算法

容错性视频转码能够在已压缩视频流中嵌入容错性工具,以增强视频流面向无线信道的抗误码能力.但是容错性工具的嵌入在降低失真的同时也会增加码率,因此需要进行率失真优化.针对这一问题,文中提出了一种基于分层率失真优化的容错性转码算法.该算法通过在帧层和宏块层分别对重同步标记的插人和帧内宏块的刷新进行不同粒度的优化来提高算法的灵活性,通过在帧层考虑帧内宏块刷新、帧内预测和运动矢量预测的影响来提高算法的精确性,通过在宏块层减少候选模式的数量来降低算法的复杂度.实验表明,该算法与基于单层率失真优化的算法相比,信噪比可获得0.6～1.1dB的增益,复杂度最多可降低25%.     

VideoAcM: a transitive and temporal access control mechanism for collaborative video database production applications

Access control models play an important role in database management systems. In general, there are three basic access control models: Discretionary Access Control (DAC), Mandatory Access Control (MAC), and Non-Discretionary Access Control (NAC). Currently, the majority of commercial DBMSs provide only DAC, and some temporal access control models have been derived based on either DAC or NAC. In the context of video database applications, since the structure of video data is complex in nature, it requires a specific and tailor-made access control mechanism which should include MAC as well as DAC and NAC. However, only few efforts have been put on access control models for video database systems. In this paper, a transitive and temporal access control mechanism for collaborative video database production applications has been proposed, which subsumes the properties of DAC, MAC, and NAC. Moreover, our proposed mechanism is integrated with the intellectual property concerns by constructing an access control hierarchy of video data with authorization rules. In particular, our mechanism can derive novel authorization rules not only on conventional client-data access control, but also on data–data access control. Besides video data, the proposed model is applicable to other data types which exhibit a hierarchical data structure.     

A secure framework of the surveillance video network integrating heterogeneous video formats and protocols

Recently, IT technologies are becoming focused on different traditional industries. The large scaled intelligent video surveillance system is one of them and it integrates a large number of digitalized CCTV [1] devices through the Web. However, existing video devices have been deployed for many years by different vendors as different models with different specifications. To integrate these heterogeneous devices, the centralized management server (CMS) and its clients need a specialized architecture to deal with different types of media encodings and connection protocols etc. In particular, well-defined access control mechanism is required for a large scaled surveillance video network. In this paper, we designed and implemented a server that incorporates the architecture integrating and delivering multiple video streams from different types of video devices to multiple clients and securing the access to the video streams.     

Optimal adaptive channel scheduling for scalable video broadcasting over MIMO wireless networks

Video broadcasting is an efficient way to deliver video content to multiple receivers. However, due to heterogeneous channel conditions in MIMO wireless networks, it is challenging for video broadcasting to map scalable video layers to proper MIMO transmit antennas to minimize the average overall video transmission distortion. In this paper, we investigate the channel scheduling problem for broadcasting scalable video content over MIMO wireless networks. An adaptive channel scheduling based unequal error protection (UEP) video broadcasting scheme is proposed. In the scheme, video layers are protected unequally by being mapped to appropriate antennas, and the average overall distortion of all receivers is minimized. We formulate this scheme into a non-linear combinatorial optimization problem. It is not practical to solve the problem by an exhaustive search method with heavy computational complexity. Instead, an efficient branch-and-bound based channel scheduling algorithm, named TBCS, is developed. TBCS finds the global optimal solution with much lower complexity. The complexity is further reduced by relaxing the termination condition of TBCS, which produces a (1 − ε)-optimal solution. Experimental results demonstrate both the effectiveness and efficiency of our proposed scheme and algorithm. As compared with some existing channel scheduling methods, TBCS improves the quality of video broadcasting across all receivers significantly.     

Content-aware rate allocation for efficient video streaming via dynamic network utility maximization

Nowadays it is vital to design robust mechanisms to provide QoS for multimedia applications as an integral part of the network traffic. The main goal of this paper is to provide an efficient rate control scheme to support content-aware video transmission mechanism with buffer underflow avoidance at the receiver in congested networks. Towards this, we introduce a content-aware time-varying utility function, in which the quality impact of video content is incorporated into its mathematical expression. Moreover, we analytically model the buffer requirements of video sources in two ways: first as constraints of the optimization problem to guarantee a minimum rate demand for each source, and second as a penalty function embedded as part of the objective function attempting to achieve the highest possible rate for each source. Then, using the proposed analytical model, we formulate a dynamic network utility maximization problem, which aims to maximize the aggregate hybrid objective function of sources subject to capacity and buffer constraints. Finally, using primal–dual method, we solve DNUM problem and propose a distributed algorithm called CA-DNUM that optimally allocates the shared bandwidth to video streams. The experimental results demonstrate the efficacy and performance improvement of the proposed content-aware rate allocation algorithm for video sources in different scenarios.     

Design issues of uplink media access control (MAC) protocols for multimedia traffic over DS-CDMA systems

We propose an efficient uplink media access control (MAC) protocol for a variable spreading gain interference-limited wideband CDMA system. It can, with high spectral efficiency, support both real-time traffic like speech and video and also nonreal-time data traffic based on packet transmission. The schemes for power allocation, joint scheduling, and transmission rate adaptation for nonreal time data traffic are designed as integrated parts of the MAC, working together to improve the system performance in terms of capacity and delay. With these associated resource management mechanisms, the performances of the MAC protocol with two different channel-allocation methods for real-time traffic are numerically compared. One is demanding channel allocation, and the other is reserve channel allocation, in which a certain bandwidth is reserved for concurrent real-time traffic.     

基于粒子群的CDMA功率和速率联合控制算法

提出了基于效用函数的CDMA网络下行链路的功率和速率联合控制最优化算法.在这类算法中,效用函数为非凸函数,经典的最优化理论很难解决这类问题.将粒子群优化方法应用于算法的非凸性设计,并通过仿真算例证明了该算法能有效解决非凸优化问题,且可保证系统的公平性.     

Cross-Layer prioritized H.264 video packetization and error protection over noisy channels

Video transmission over wireless channels is affected by channel-induced packet losses. Distortion due to channel errors can be alleviated by applying forward error correction. Aggregating H.264/AVC slices to form video packets with sizes adapted to their importance can also improve transmission reliability. Larger packets are more likely to be in error but smaller packets require more overhead. We present a cross-layer dynamic programming (DP) approach to minimize the expected received video distortion by jointly addressing the priority-adaptive packet formation at the application layer and rate compatible punctured convolutional (RCPC) code rate allocation at the physical layer for prioritized slices of each group of pictures (GOP). Some low priority slices are also discarded to improve protection to more important slices and meet the channel bit-rate limitations. We propose two schemes. Our first scheme carries out joint optimization for all slices of a GOP at a time. The second scheme extends our cross-layer DP-based approach to slices of each frame by predicting the expected channel bit budget per frame for live streaming. The prediction uses a generalized linear model developed over the cumulative mean squared error per frame, channel SNR, and normalized compressed frame bit budget. The parameters are determined over a video dataset that spans high, medium and low motion complexity. The predicted frame bit budget is used to derive the packet sizes and corresponding RCPC code rates for live transmission using our DP-based approach. Simulation results show that both proposed schemes significantly improve the received video quality over contemporary error protection schemes.     

基于语音时隙机制的车载自组网MAC协议

在节点高速运动的车载组网多跳通信中,如何快速选择下一跳中继节点是目前无线自组网亟待解决的问题。为此,提出一种基于类语音时隙划分信道竞争机制的时分复用协议,采用类似语音优先权接入的语音突发方式解决多跳中继选择问题。仿真结果表明,在不同节点分布的运动场景下,使用语音突发方式的MAC协议较传统的时分复用随机接入方式具有更短的接入延时与更低的网络开销。     

一种高信道利用率的无人机自组网单阈值接入协议

为解决现有无人机自组网MAC层接入协议信道负载统计时间不统一导致负载统计结果存在误差和信道资源利用率降低的问题,提出一种多优先级单阈值接入控制(MSAC)协议.通过设计信道负载统计时间校正机制和基于单阈值的信道接入控制机制,实现更精准的信道负载统计和以数据包为单位的负载控制,使系统信道承载能力与实际信道负载相匹配,最大...