嵌入式视频监控系统实时性研究

针对目前嵌入式系统资源有限及提高视频传输实时性方案不适合嵌入式视频监控系统的情况,提出基于视频流量预测和网络带宽检测的提高视频监控系统实时性方案。该方案采用线性规划视频流量预测算法和数据包的方法检测网络带宽,预测视频流量和网络带宽,据此调整视频缓存,达到提高视频实时性且节约系统资源的目标。     

面向RCBR网络的变比特率MPEG视频流的自适应预测

变比特率视频业务是将来多媒体业务的主要组成部分，为保证高质量，实时传输的需要，准确把握视频特征，结合网络传输机制为多媒体通信提供更好的服务质量（QoS)是目前亟待解决的问题之一，该文针对面向RCBR（Renegotiated Constant Bit Rate)网络的变比特率MPEG视频提出了基于编码结构的自适应预测算法，它充分利用了视频流的周期相关性，能准确快速，无延迟地对视频帧的码率进行预测，通过网络动态地为视频分配合适的带宽，不仅能达到高质量，低延迟抖动的视频服务，并且提高了网络的利用率，与分配固定带宽的网络相比，其网络缓冲的排除性能和网络的利用率有明显提高。     

Bandwidth allocation in UWB WPANs with ECMA-368 MAC

The new ECMA-368 MAC for UWB WPANs consists of two channel access methods: the distributed reservation protocol (DRP) and prioritized contention access (PCA). The exact method of medium access slot (MAS) allocation in DRP is not specified in the standard. The contribution of this paper is twofold. First, the paper describes a distributed resource allocation method in which a number of interference–avoidance rules are used to reserve slots for devices. Devices maintain sending and receiving tables to track activities in the neighbourhood. The proposed method is a simple, effective solution to the DRP MAS allocation problem, avoiding reservation conflicts and interference from hidden terminals. Secondly, for VBR MPEG-4 video traffic, we propose a bandwidth requirement calculation method based on traffic prediction. In the proposed scheme bandwidth is allocated based on accurate traffic predictions, therefore matching network resources to the traffic demand. Application QoS is maintained while network utilization is kept high. Furthermore, the simple, adaptive linear predictor does not incur much computation overhead. Simulation results have demonstrated the accuracy of the proposed prediction algorithm and effectiveness of the bandwidth allocation method.     

Presenting a traffic management and control system in driver assistance form based on vehicular networks

Vehicular Networks is considered a major step in the field of Intelligent Transportation System (ITS). In this technology, some equipment will be installed on vehicles and special places at roadsides which will enable the wireless communication between vehicles with each other and will provide the communication between the vehicles and roadside equipment. One of the ITS application is Traffic monitoring system. Such system enables accessing traffic videos by traffic monitoring centers to make traffic decision. However, providing traffic video for the vehicles can be appealing. This paper addresses a new application in vehicular networks and ITS which can provide this videos for drivers in a city. Each driver request timely traffic video of a location from a web server and the web server forward this request to a stream management server. This server based on current location of the requester vehicle, its speed and its direction calculates appropriate video chunks for each RSU along vehicle destination. This study aims to present a system which can bring a high accessibility for content and can provide it with an appropriate bandwidth and quality for vehicles. Due to the scalability and bandwidth limitations for its content and streaming, vehicular networks are used in this system.     

Traffic characterization algorithms for VBR video in multimedia networks

A network that offers deterministic, i.e., worst case, quality-of-service guarantees to variable-bit-rate (VBR) video must provide a resource reservation mechanism that allocates bandwidth, buffer space, and other resources for each video stream. Such a resource reservation scheme must be carefully designed, otherwise network resources are wasted. A key component for the design of a resource reservation scheme is the traffic characterization method that specifies the traffic arrivals on a video stream. The traffic characterization should accurately describe the actual arrivals, so that a large number of streams can be supported; but it must also map directly into efficient traffic-policing mechanisms that monitor arrivals on each stream. In this study, we present a fast and accurate traffic characterization method for stored VBR video in networks with a deterministic service. We use this approximation to obtain a traffic characterization that can be efficiently policed by a small number of leaky buckets. We present a case study where we apply our characterization method to networks that employ a dynamic resource reservation scheme with renegotiation. We use traces from a set of 25–30-min MPEG sequences to evaluate our method against other characterization schemes from the literature.     

Content-Aware Distortion-Fair Video Streaming in Congested Networks

Internet is experiencing a substantial growth of video traffic. Given the limited network bandwidth resources, how to provide Internet users with good video playback quality-of-service (QoS) is a key problem. For video clips competing bandwidth, we propose an approach of Content-Aware distortion-Fair (CAF) video delivery scheme, which is aware of the characteristics of video frames and ensures max-min distortion-fair sharing among video flows. CAF leverages content-awareness to prioritize packet dropping during congestion. Different from bandwidth fair sharing, CAF targets end-to-end video playback quality fairness among users. The proposed CAF approach does not require rate-distortion modeling of the source, which is difficult to estimate. Instead, it exploits the temporal prediction structure of the video sequences along with a frame drop distortion metric to guide resource allocations and coordinations. Experimental results show that the proposed approach operates with limited overhead in computation and communication, and yields better QoS, especially when the network is congested.     

Dynamic Fuzzy Controlled RWA Algorithm for IP/GMPLS over WDM Networks

This paper proposes a dynamic RWA scheme using fuzzy logic control on IP/GMPLS over WDM networks to achieve the best quality of network transmission. The proposed algorithm dynamically allocates network resources and reserves partial bandwidth based on the current network status, which includes the request bandwidth, average utilization for each wavelength and its coefficient of variance (C.V.) of data traffic, to determine whether the connection can be set up. Five fuzzy sets for request bandwidth, average rate and C.V. of data traffic are used to divide the variable space: very large (LP), large (SP), normal (ZE), small (SN), and very small (LN). Setting the fuzzy limit is a key part in the proposed algorithm. The simulation of scenarios in this paper has two steps. In the first step, the adaptive fuzzy limits are evaluated based on average transmission cost pertaining to ten network statuses. The second step is to compare the proposed algorithm with periodic measurement of traffic (PMT) in ATM networks in six network situations to show that the proposed FC-RWA algorithm can provide better network transmission.     

Dynamic resource management considering the real behavior ofaggregate traffic

This paper explains why the theory of effective bandwidth is in general not applicable to characterize realistic traffic sources. Moreover, we show that a static allocation of network resources (bandwidth and/or buffer space) based on large deviation theory can be highly inefficient when the real statistical behavior of traffic is taken into account. As an alternative, we propose a dynamic resource management scheme based on prediction techniques. As a specific example, we apply this scheme to a Differentiated Service (DiffServ) Internet environment, in which the goal, besides policing the incoming traffic, is to optimize the use of network resources, thus minimizing the probability of occurrence of violations of contract guarantees. The performance of the proposed scheme is evaluated via simulations and our results show the superior performance of the new algorithm in terms of buffer overflows, output link utilization, and jitter, as compared to currently used policing and shaping mechanisms     

Admission control for media on demand services

Admission control software is used to make accept or deny decisions about incoming service requests to avoid overload. Existing media streaming software includes only limited support for admission control by allowing for predefined static rules. Such rules limit for example the number of requests that are allowed to enter the system during a certain time or define thresholds concerning the utilization level of a single resource such as network bandwidth. In media streaming applications, however, the bottleneck resource (CPU, Disk I/O, network bandwidth, etc.) might change over time depending on the current demand for different types of audio or video files. This paper proposes a model for adaptive admission control in the presence of multiple scarce resources. Opportunity costs for a service request are determined at the moment of an incoming request and compared to the revenue of a request in order to make an accept/deny decision. Opportunity costs are based on resource utilization, service resource requirements, expected future demand for services, and the revenue per accepted service. The model allows rejection of service requests early to reserve capacity required to perform future service requests with higher revenues. We describe a number of experiments to illustrate the benefits of adaptive admission control models over static admission control rules.     

基于网络流量预测的DASH系统优化

近年来基于超文本传输协议（HTTP）的自适应视频流量大幅上升,传统HTTP动态自适应流（DASH）速率算法无法准确预测网络吞吐量,导致网络带宽波动,使传输控制协议慢启动并触发抛弃规则,从而降低视频质量。提出一种基于网络流量预测的改进DASH速率算法。将DASH算法分为视频质量选择阶段、视频下载阶段和请求等待阶段,在视频质量选择阶段引入支持向量回归模型和长短期记忆网络预测网络吞吐量,结合缓冲时长选择更优质量的视频片段,在视频下载阶段通过预测实时吞吐量降低触发抛弃规则的次数。仿真结果表明,该算法可自适应流速率并减少抛弃规则的命中次数,有效提高视频体验质量。     

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.      

一种移动流媒体分层协同缓存系统

随着移动互联网的发展和用户数量的增加,网络中的音视频服务普遍采用动态缓存机制来减轻回程主干网的带宽压力和提高用户的观影体验。如何根据网络和用户需求,调整不同节点的缓存内容,以减少主干网的带宽压力,是当前缓存部署迫切需要解决的问题。基于子模函数理论,本文提出主动和被动资源分配调整方案及其算法。主动方案根据资源的流行度把视频文件部署到缓存节点上,以达到用户访问代价的最小化;被动方案根据音视频流行度的变化对节点上缓存的内容进行实时调整,以提高缓存资源的利用率和用户体验,降低主干网的带宽消耗。最小访问代价算法的复杂度与缓存空间容量大小相关,在缓存空间紧张时能快速迭代出资源的分配方案。数值仿真表明,主动和被动分配资源分配方案能有效降低远程服务器的带宽压力和提高用户体验。     

Design, Analysis, and Implementation of a Novel Low Complexity Scheduler for Joint Resource Allocation

Over the past decade, the problem of fair bandwidth allocation among contending traffic flows on a link has been extensively researched. However, as these flows traverse a computer network, they share different kinds of resources (e.g., links, buffers, router CPU). The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. Moreover, conventional resource scheduling algorithms depend strongly upon the assumption of prior knowledge of network parameters and cannot handle variations or lack of information about these parameters. In this paper, we present a novel scheduler called the composite bandwidth and CPU scheduler (CBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. CBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Analytically, we prove that CBCS is efficient, with a per-packet work complexity of O(1). Finally, we present simulation results and experimental outcomes from a real-world implementation of CBCS on an Intel IXP 2400 network processor. Our results highlight the improved performance achieved by CBCS and demonstrate the ease with which it can be implemented on off-the-shelf hardware     

A research on dynamic allocation of network resources based on P2P traffic planning

With the rapid development of P2P applications, its consumption of bandwidth resources brought increasing pressures to ISPs. How to manage P2P traffic efficiently, both to improve the efficiency of network and to protect the interests of P2P users, is widely concerned by industry and academia. Although some traffic planning scheme to the P2P apps such as P4P can alleviate the pressure on bandwidth resources to some extent, it requires deep cooperation between ISPs and P2P service providers. Therefore it has some limitations to independent DPI strategies. In addition, there is no flow planning strategies which can rapidly response to ISPs’ QOS requirements such as sudden changes of bandwidth reservation and so on. This paper analyses current mainstream P2P optimization strategies, and then put forward a network resources dynamic allocation (NRDA) technology based on the deployment of P2P traffic stand on the ISPs’ position. This technology enables ISPs to have the ability to manage the P2P traffic on the specified links independently and efficiently, especially for the rapid response of unexpected resource requirements. NRDA implements an overall planning of network resources and makes the network flexible, provides the resource planning ability to the ISPs.     

一种灵活的IaaS云服务租户带宽保障模型

针对云数据中心中基础设施即服务（IaaS）的租户带宽保障问题,提出了租户需求模型弹性带宽保障模型（EBG）。提出了以往研究中没有涉及到的租户需求扩展问题。EBG模型通过解耦合网络与计算资源提供了灵活性,能更有效地利用网络资源,同时解决了租户扩展问题。设计实现了EBG模型的部署算法,通过模拟实验证实了新模型能够更好地利用网络带宽资源,同时减少因为租户扩展需求造成的虚拟机迁移问题。     

实时视频传输带宽的自适应在线调整策略

通过实验表明,动态地根据实时视频流的低频信号部分进行带宽“在线”预测和调整,在网络利用率方面远优于根据视频流峰值速率进行的静态带宽分配。文中着重分析比较了以下两种带宽预测算法:(1)AR时间序列模型;(2)改进型BP神经网络模型。     

一种自适应的视频流化前向纠错算法

网络视频应用经常会受到数据包丢失或错误以及网络带宽资源不足的干扰.相关研究表明:在多数情况下,动态变化的网络带宽和丢包率是影响视频流化质量的关键因素.因此,为了保证视频质量,可以采用前向纠错(forward error correction,简称FEC)编码来提高视频数据传输的可靠性;同时,为了适应网络状态的变化,发送端可以调节视频数据的发送速率,并在视频源数据与FEC数据之间合理分配网络传输带宽.首先通过对视频流结构的分析,在充分考虑帧之间的依赖关系和帧类型的基础上提出了一种帧的解码模型.在此基础上,建立了用于在视频源数据和FEC数据之间分配网络带宽资源的优化算法.实验表明,该模型可以有效地适应网络状态的变化,并通过优化分配网络带宽资源来使接收端获得最大的可播放帧率.     

基于预测机制的云媒体网络自适应视频流选择算法

研究移动网络中,如何进一步提高云媒体服务带宽利用率的问题,提出一种基于预测机制的云媒体网络自适应视频流选择算法。该算法包含可用带宽预测模型和视频流决策模型。在带宽预测模型中,根据带宽评估结果把当前的网络状态划分为三个模式,每个模式对应不同的带宽预测方法,并且不同的模式能够相互转化。在视频流决策模型中,利用预测的可用带宽,结合可伸缩视频编码技术为用户自适应的调整视频质量。根据实验,在不同网络环境下,该方法能够有效的利用带宽,并提高媒体服务质量。     

An embedded fuzzy expert system for adaptive WFQ scheduling of IEEE 802.16 networks

WiMAX is a futuristic technology which provides simultaneous support for web, video, and voice applications. WiMAX networks are best suitable to real time traffic however the quantity of non real time and best effort traffic cannot be neglected. Distribution of resources in such heterogeneous applications is therefore a challenging task. There are many schedulers available for WiMAX but adaptive and adequate schedulers are still in growing stage of development. This paper introduces a novel method using which a system is developed based on concepts of fuzzy logic to schedule traffic in WiMAX networks. The proposed fuzzy expert system simplifies fair allocation of resources to real as well as non real time traffic. The implementation is based on changing the weights of the queues serving real and non- real time traffic adaptively. New weights will be calculated for each bandwidth request made to base station and these weights will in turn decide amount of bandwidth allocated to different traffic classes. The weights are calculated based on three parameters that are amount of real time and non real time traffic in queues, change in throughput requirement for non real time flows and latency requirement of real time input data. Results obtained by virtue of simulations justify the significance of the proposed method.     

A novel resource scheduling algorithm for QoS-aware services on the Internet

The popularity and availability of Internet connection has opened up the opportunity for network-centric collaborative work that was impossible a few years ago. Contending traffic flows in this collaborative scenario share different kinds of resources such as network links, buffers, and router CPU. The goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. In this paper, firstly, we present a novel QoS-aware resource scheduling algorithm called Weighted Composite Bandwidth and CPU Scheduler (WCBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. WCBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Secondly, we present some analytical results, extensive NS-2 simulation work, and experimental results from our implementation on Intel IXP2400 network processor. The simulation and implementation results show that our low complexity scheduling algorithm can efficiently maximise the CPU and bandwidth utilisation while maintaining guaranteed Quality of Service (QoS) for each individual flow.