Packet Permutation: A Robust Transmission Technique for Continuous Media Streaming Over the Internet

With the growing popularity of the Internet, there is an increasing demand to deliver continuous media (CM) streams over the Internet. However, packets may be damaged or lost during transmission over the current Internet. In particular, periodic network overloads often result in bursty packet losses, degrading the perceptual quality of CM streaming. In this paper, we focus on reducing the impact of this bursty loss behavior. We propose a novel robust end-to-end transmission scheme, referred to as packet permutation (PP), to deliver pre-compressed continuous media streams over the Internet. At the server side, PP permutes, prior to transmission, the normal packet delivery sequence of CM streams in a specific way. The packets are then re-permuted at the receiver side before they are presented to the application. In this way, the probability of losing a large number of packets within each CM frame can be significantly reduced. To validate the effectiveness of PP, a series of trace-driven simulations are conducted. Our results show that for a given quality of service (QoS) requirement of CM streaming, PP greatly reduces the overhead required by traditional error control schemes, such as forward error correction (FEC) and feedback/retransmission-based schemes.     

The cache assignment problem and its application to database buffermanagement

Given N request streams and L⩽N LRU caches, the cache assignment problem asks to which cache each stream should be assigned in order to minimize the overall miss rate. An efficient solution to this problem is provided, based on characterizing each stream using the stack reference model and characterizing the interaction of the streams using a bursty stream model. It is shown that for Bernoulli (purely random) mixing of streams, the optimal cache assignment is to have one cache per stream. In practice streams are mixed in a way that is much “burstier” than can be represented by the Bernoulli model. Therefore a method is presented for superposition of bursty streams. The performance of the methods developed for bursty stream superposition and cache assignment are tested using trace data obtained from the database system DB2. The resulting cache assignment recommendations are then applied to the DB2 system, and considerable performance improvement is found to result     

复合流式媒体的同步与带宽自适应的研究

提出了一种在客户端进行同步控制的方案，采用基于流内同步的流间同步方法，可以实现多个流媒体的同步播放，并且能够对信道带宽变化作出反应，根据多个流媒体之间的优先级关系自动调整各个流媒体的比特率，保证整体播放质量。     

Super-Streaming: A New Object Delivery Paradigm for Continuous Media Servers

A number of studies have focused on the design of continuous media, CM, (e.g., video and audio) servers to support the real-time delivery of CM objects. These systems have been deployed in local environments such as hotels, hospitals and cruise ships to support media-on-demand applications. They typically stream CM objects to the clients with the objective of minimizing the buffer space required at the client site. This objective can now be relaxed due to the availability of inexpensive storage devices at the client side. Therefore, we propose a Super-streaming paradigm that can utilize the client side resources in order to improve the utilization of the CM server. To support super-streaming, we propose a technique to enable the CM servers to deliver CM objects at a rate higher than their display bandwidth requirement. We also propose alternative admission control policies to downgrade super-streams in favor of regular streams when the resources are scarce. We demonstrate the superiority of our paradigm over streaming with both analytical and simulation models.Moreover, new distributed applications such as distant-learning, digital libraries, and home entertainment require the delivery of CM objects to geographically disbursed clients. For quality purposes, recently many studies proposed dedicated distributed architectures to support these types of applications. We extend our super-streaming paradigm to be applicable in such distributed architectures. We propose a sophisticated resource management policy to support super-streaming in the presence of multiple servers, network links and clients. Due to the complexity involved in modeling these architectures, we only evaluate the performance of super-streaming by a simulation study.     

A buffer-inventory-based dynamic scheduling algorithm for multimedia-on-demand servers

We present a producer-consumer model of multimedia-on-demand (MOD) servers. The producer retrieves media data from a disk and places it into a set of buffers, while the consumer sends out the data in the buffers to the users. We develop for the producer a buffer-inventory-based dynamic scheduling (BIDS) algorithm that guarantees non-zero inventory and non-overflow of data in the buffers to meet the continuity requirement and no-loss of data for each media stream. The algorithm can deal with heterogeneous me dia streams as well as the transient circumstances upon service completions and arrivals of new requests. To smooth out the impact of bursty data of variable-bit-rate media streams and therefore increase the maximum admissible load of requests, we also introduce into the scheduling scheme a time-scale-dependent peak consumption rate and a virtual cycle time. Based on BIDS, an effective admission control mechanism can be easily established by checking two simple conditions respectively on the overall system load and buffer size. Our algorithm is very easy to implement. Experiments carried out with an actual disk system and real video stream data verify that it is more robust compared to static scheduling algorithms previously proposed in the literature, especially when handling variable-bit-rate media streams.     

基于运动矢量差（MVD）的CABAC新算法*

在H.264/AVC视频编码标准中,基于上下文的自适应二进制算术编码（CABAC）主要应用于主要档次中,并且具有较高的压缩效率。首先分析了CABAC编码原理和运动矢量差（MVD）各分量的上下文模型选择原理,而后提出了在帧间编码分割块尺寸下,充分地利用当前块MVD与当前块MV的相关性、当前块MVD与已编码相邻块MVD的相关性以及当前块MVD中各分量之间相关性的CABAC优化算法（CABAC₁算法）。通过实验表明:较基准CABAC算法,CABAC₁算法一方面能有效地降低2%左右的编码时间及确保了编码序列的视觉质量;另一方面能够有效地节约在编码中帧间编码帧的码流（比特流）,其中P帧平均节约了10%左右的比特流,B帧节约了5%左右的比特流。因此,CABAC₁算法是一种有效的优化算法。     

基于向量表示和标签传播的半监督短文本数据流分类算法

社交网络平台产生海量的短文本数据流,具有快速、海量、概念漂移、文本长度短小、类标签大量缺失等特点.为此,文中提出基于向量表示和标签传播的半监督短文本数据流分类算法,可对仅含少量有标记数据的数据集进行有效分类.同时,为了适应概念漂移,提出基于聚类簇的概念漂移检测算法.在实际短文本数据流上的实验表明,相比半监督分类算法和半监督数据流分类算法,文中算法不仅提高分类精度和宏平均,还能快速适应数据流中的概念漂移.     

基于突发特征分析的事件检测*

针对新闻数据流的事件检测问题,提出了一种基于突发特征分析的事件检测方法。事件由在一定时间窗口内代表它的特征构成,通常它们在事件发生时表现出一定的突发。通过多尺度突发分析算法识别出突发特征,并计算突发特征突发模式的相似性及所在新闻的重合度,对突发特征进行聚类分析以构造事件。在路透社80多万篇新闻数据集中验证上述算法,可准确地识别出突发特征各种跨度上的突发,且能有效地检测出事件。     

Wavelet-based VBR video traffic smoothing

In a typical video application, such as video-on-demand, videos are continuously streamed from a video server to a distributed set of receivers. The constant-quality video compression technique commonly used, variable bit rate (VBR) encoding, produces flows with multiple time-scale rate variability, so smoothing the VBR video traffic within an entire distribution tree presents a challenging task. This paper proposes a novel wavelet-based traffic smoothing (WTS) algorithm. Unlike existing algorithms, the WTS algorithm considers traffic smoothing at multiple resolutions. It results in a pruned version of a full tree, which corresponds to the original VBR traffic. Theoretical analysis and numerical evaluation demonstrate that: 1) WTS performs well across several metrics in smoothing bursty traffic and 2) for a video bit stream with N frames, the computational complexity of WTS is O(NlogN).     

Synchronized delivery and playout of distributed stored multimedia streams

Multimedia streams such as audio and video impose tight temporal constraints for their presentation. Often, related multimedia streams, such as audio and video, must be presented in a synchronized way. We introduce a novel scheme to ensure the continuous and synchronous delivery of distributed stored multimedia streams across a communications network. We propose a new protocol for synchronized playback and compute the buffer required to achieve both, the continuity within a single substream and the synchronization between related substreams. The scheme is very general and does not require synchronized clocks. Using a resynchronization protocol based on buffer level control, the scheme is able to cope with server drop-outs and clock drift. The synchronization scheme has been implemented and the paper concludes with our experimental results.     

无线传感器网络中时间同步技术的综述

时间同步技术是无线传感器网络中非常重要的协议之一,也是其他协议可靠运行的前提条件,近年来也有相当多的同步机制被提出来,在大规模的无线传感器网络中,单跳同步误差的累加,时钟偏移与漂移同时补偿,同步机制的拓扑性能,同步收敛速度等是目前同步机制研究过程中的主要挑战,传统的集中式同步机制无法满足大规模无线传感器网络的性能要求,研究者们也提出了梯度同步机制,协作同步机制,以及分步式同步机制等来应对这些挑战.本文详细的分析了这些同步机制,并探讨了未来可能的发展方向.     

Boosting decision stumps for dynamic feature selection on data streams

Feature selection targets the identification of which features of a dataset are relevant to the learning task. It is also widely known and used to improve computation times, reduce computation requirements, and to decrease the impact of the curse of dimensionality and enhancing the generalization rates of classifiers. In data streams, classifiers shall benefit from all the items above, but more importantly, from the fact that the relevant subset of features may drift over time. In this paper, we propose a novel dynamic feature selection method for data streams called Adaptive Boosting for Feature Selection (ABFS). ABFS chains decision stumps and drift detectors, and as a result, identifies which features are relevant to the learning task as the stream progresses with reasonable success. In addition to our proposed algorithm, we bring feature selection-specific metrics from batch learning to streaming scenarios. Next, we evaluate ABFS according to these metrics in both synthetic and real-world scenarios. As a result, ABFS improves the classification rates of different types of learners and eventually enhances computational resources usage.     

概念漂移数据流半监督分类综述

在开放环境下,数据流具有数据高速生成、数据量无限和概念漂移等特性.在数据流分类任务中,利用人工标注产生大量训练数据的方式昂贵且不切实际.包含少量有标记样本和大量无标记样本且还带概念漂移的数据流给机器学习带来了极大挑战.然而,现有研究主要关注有监督的数据流分类,针对带概念漂移的数据流的半监督分类的研究尚未引起足够的重视....     

Synchronization-Sensitive Frame Estimation: Video Quality Enhancement

Network transmission is liable to errors and data loss. In movie transmission, packets of video frames are subject to loss or even explicit elimination for many reasons including congestion handling and the achievement of higher compression. Not only does the loss of video frames cause significant reduction in video quality, but it could also cause a loss of synchronization between the audio and video streams. If not corrected, this cumulative loss can seriously degrade the motion picture's quality beyond viewers' tolerance. In this paper, we study and classify the effect of audio-video de-synchronization. Afterwards, we develop and examine the performance and appropriateness of the application of many client-based techniques in the estimation of lost frames using the existing received frames, without the need for retransmissions or error control information. The estimated frames are injected at their appropriate locations in the movie stream to restore the loss. The objective is to enhance video quality by finding a very close estimate to the original frames at a suitable computation cost, and to contribute to the restoration of synchronization within the tolerance level of viewers.     

Online smoothness with dropping partial data based on advanced video coding stream

Most studies of smoothing video stream compute the required bit rate of video transmission to satisfy all the transmitted data. In this paper, our proposed online smoothing with tolerable data dropping algorithm can adjust the bit rate as smooth as possible. Several multimedia encoding schemes, such as advanced video coding (AVC), can support partial data dropping to adapt to available bandwidth network. The AVC stream can be adapted by smoothing algorithm to ensure video quality for a given set of constraints where these constraints may be either static after the session set up or may dynamically change over the session duration. Our algorithm is based on the online minimum variance bandwidth allocation algorithm to look ahead a window of frames, dynamically adjusting the required bit rate such that ensuring smoothness when the buffer encounters underflow or overflow for video stream. Furthermore, we add the scheme of data dropping into this algorithm to increase the possibility of smoothing bit rates. The experimental results show the peak rate, the average ratio of dropped data, and the coefficient of variation for five test sequences with different content characteristics such as the average frame size, the peak/mean ratio of frame size, and the average frame bit rate. Experimental parameters are varied by window sizes and tolerable dropping ratios. The algorithm can significantly reduce the peak rate and the coefficient of variation when the transmitted packets are allowed dropping by a user-defined dropping ratio.     

基于分簇的低功耗多跳WSN时间同步机制

针对典型同步算法中同步开销大的问题,提出一种基于分簇的低功耗时间同步机制(LCTS),将单向广播同步和双向成对同步机制相结合,在分级网络的基础上给出一种分簇算法,将LCTS扩展到多跳网络中,并对时钟漂移进行估计和补偿。仿真结果证明,该机制在不引起同步滞后的前提下,能减少同步报文开销,保证良好的同步精度。     

概念漂移数据流挖掘算法综述

数据流是一种新型的数据模型,具有动态、无限、高维、有序、高速和变化等特性。在真实的数据流环境中,一些数据分布是随着时间改变的,即具有概念漂移特征,称为可变数据流或概念漂移数据流。因此处理数据流模型的方法需要处理时空约束和自适应调整概念变化。对概念漂移问题和概念漂移数据流分类、聚类和模式挖掘等内容进行综述。首先介绍概念漂移的类型和常用概念改变检测方法。为了解决概念漂移问题,数据流挖掘中常使用滑动窗口模型对新近事务进行处理。数据流分类常用的模型包括单分类模型和集成分类模型,常用的方法包括决策树、分类关联规则等。数据流聚类方式通常包括基于k- means的和非基于k- means的。模式挖掘可以为分类、聚类和关联规则等提供有用信息。概念漂移数据流中的模式包括频繁模式、序列模式、episode、模式树、模式图和高效用模式等。最后详细介绍其中的频繁模式挖掘算法和高效用模式挖掘算法。     

Fundamental tradeoffs in distributed algorithms for rate adaptive multimedia streams

Rate adaptive multimedia streams adjust the encoding rate dynamically (with corresponding changes in media content resolution) in response to changing levels of congestion along the route. The field of optimization based congestion control has yielded sophisticated distributed algorithms for resource allocation among competing elastic streams. In this work we study the fundamental tradeoffs for a class of optimization based distributed algorithms for rate adaptive streams. We focus on three tradeoffs: (i) the tradeoff between maximizing client average quality of service (QoS) and client fairness, (ii) the tradeoff between granularity of control (both temporal and spatial) and QoS, and (iii) the tradeoff between maximizing the received volume and minimizing the fluctuations in received rate. We illustrate these tradeoffs through extensive ns-2 simulations on two distinct topologies – (i) a single bottleneck like and (ii) a linear network.     

基于RTP/RTCP协议的实时数据传输与同步控制策略

针对分组交换网络中的实时媒体传输,考虑非QOS保证的分组网络可能带来的传输丢包、乱序和抖动等情况,采用基于RTP/RTCP协议的媒体传输和媒体控制机制,在媒体流中添加时间戳等控制信息,通过播放时延控制算法进行媒体内同步,并在媒体内同步的基础上,根据发送方的绝对时间戳和RTP时间戳的对应关系,确定不同媒体流之间的同步点,从而达到多通道媒体间同步的效果。     

Reducing bandwidth requirement for delivering video over wide area networks with proxy server

Due to the high bandwidth requirement and rate variability of compressed video, delivering video across wide area networks (WANs) is a challenging issue. Proxy servers have been used to reduce network congestion and improve client access time on the Internet by caching passing data. We investigate ways to store or stage partial video in proxy servers to reduce the network bandwidth requirement over WAN. A client needs to access a portion of the video from a proxy server over a local area network (LAN) and the rest from a central server across a WAN. Therefore, client buffer requirement and video synchronization are to be considered. We study the tradeoffs between client buffer, storage requirement on the proxy server, and bandwidth requirement over WAN. Given a video delivery rate for the WAN, we propose several frame staging selection algorithms to determine the video frames to be stored in the proxy server. A scheme called chunk algorithm, which partitions a video into different segments (chunks of frames) with alternating chunks stored in the proxy server, is shown to offer the best tradeoff. We also investigate an efficient way to utilize client buffer when the combination of video streams from WAN and LAN is considered.