主动队列管理算法之初探

本文对现有的几种主动队列管理算法：自适应虚拟队列（AVQ）算法、动态阈值（DT）算法以及队列长度阈值（QLT）分组调度算法等进行了介绍,并对其进行了简单的分析和比较。最后针对AVQ算法进行了改进,使其在原性能的基础上增加了区分服务的功能。     

QPID-AVQ：一种基于队列的PID控制的AVQ算法

本文针对AVQ算法存在的不足,在PD-AVQ算法基础上,为进一步提高系统的稳定性,引入积分选项,构成PID-AVQ算法,运用控制理论推导出了满足系统稳定条件的取值范围.利用PID-AVQ算法更新虚拟带宽,综合考虑平均队列长度和包到达速率,提出了一种新的基于队列的PID控制自适应虚拟队列管理算法QPID-AVQ,可根据网络实际情况调节参数,保持队列长度稳定.仿真结果表明,当控制参数在稳定范围内取值时,QPID-AVQ算法能较好地适应网络状态变化,使队列长度始终维持在期望值附近,而不受用户数量的影响,具有较好的稳定性、抗干扰能力和较高的带宽利用率,综合性能优于PD-AVQ和RED算法.     

PDAVQ：一种基于PD控制的自适应虚拟队列管理算法

提出了一种新的基于比例差分控制的自适应虚拟队列管理(AVQ)算法—PDAVQ,用于对网络链路中产生的拥塞进行控制,以达到有效利用网络带宽,使整个网络系统达到稳定,缓解网络拥塞的目的。而且本文对所提算法运用控制理论对系统的稳定性进行了证明,给出了满足系统稳定性条件的参数选择方法和 PDAVQ 算法的具体描述。最后,通过 ns2 仿真实验与现有的 AVQ 算法比较,结果表明,所提 PDAVQ 算法具有较高的吞吐率、较低的链路延迟和数据丢失率,并能更快的使整个网络系统达到稳定,具有较好的网络性能。     

一种基于动态阈值的主动队列管理算法

针对BLUE算法缺少早期拥塞检测机制,导致队列溢出或空闲现象频繁发生的问题,通过引进基于动态阈值算法的控制机制,借鉴RED算法所采用的早期拥塞检测机制,提出了DT-BLUE算法。仿真实验表明本文算法能保持队列长度的稳定性,有效降低队列空闲或溢出现象的发生,提高链路的利用率。     

一种低延迟的可扩展调度算法

提出了一种基于阈值的分布式迭代算法。与现有算法不同的是,该算法针对可扩展网络交换调度结构的特点,为处于最高优先级的调度器安排了2次迭代,第1次迭代用阈值方法找出一些较长的VOQ（虚拟输出队列）,并在最高优先级时隙之前的一个时隙完成,以缩短信号的处理时间。仿真结果表明,该算法与现有算法相比,在大流量的uniform流量模式下,延时性能和吞吐率获得了明显的提高。同时,该算法的硬件代价小,有效地实现了性能和复杂度的良好折中。     

二进制堆排序算法的改进研究

基于对网络服务质量中队列调度算法的介绍和分析,从队列的优先级角度出发,对经典的二进制堆Heap调度排序算法进行了改进,提出了一种新的Heap＋算法,该算法充分利用原算法出队、入队操作数固定的特点,使其在保证硬件实现复杂度低的情况下能够做到出队、入队操作的流水化,从而达到高度的并行性。且具备很高的资源利用率和可扩展性,可用于高速链路上高精度虚拟时间的排序操作。     

主动队列管理算法性能评价：比较研究

对当前的主动队列管理算法进行了分类，然后基于NS2网络仿真器比较了它们在不同流量和网络拓扑条件下的多种性能指标。主要结论包括：ARED综合表现最好；PI和REM的瞬态性能较差，对动态流量响应较慢：REM和没有ECN支持的AVQ可以得到较小的时延，但同时牺牲了链路的带宽利用率并造成大量分组丢失；在多瓶颈网络拓扑中，大部分算法的性能有所提高。     

基于优先队列的最小生成树算法

本文提出一个获取连通网络是小生成树的算法。该算法采用一个优先队列组织各顶点集合，每次根据边的权值对队列头集合进行增长。由于对每个顶点的相关联边进行了按权值分级排序的预处理，算法获取具有。个预示e条边的无向连通网络的最小生成树的期望时间是O（e*loglogn）。     

支持优先级与公平策略的队列规程

首先介绍了队列调度算法在流量控制中的关键地位,然后讨论了现有队列调度算法,如基于优先级的调度算法、轮询调度算法与公平队列调度算法,最后提出了一种新的队列规程,该队列规程融合了优先级调度算法与DRR调度算法。在网络正常情况下,不同业务流公平地共享网络带宽,在网络出现拥塞的情况下,高优先级业务流能够抢占带宽,保证其较低的丢包率,并能够实现两种调度算法的快速切换。     

分布式队列服务算法在无线网状网包调度中的应用

根据无线网状网的包调度特点,结合已有的差分队列服务算法和分布式贝尔曼-福特算 法,将有线网络中的差分队列服务算法改进为分布式队列服务算法（DQS）,使之实用于无 线网状网中多任务条件下实现系统的吞吐量最大化。仿真实验证明了DQS算法能有效地避免 传统多径传输中的按“类”或 “流”来进行调度的缺陷,有效地减少了数据包的端到端 延时和缓冲区需求,尤其是DQS算法的实际平均吞吐量性能有了很大的提高。     

Stability analysis in an AVQ model of Intemet congestion control algorithm

This paper focuses on the local stability of a classical congestion control model in the Internet,namely adaptive virtual queue(AVQ) algorithm with feedback delay.Firstly,necessary and sufficient stability conditions in terms of key tuning parameters are given,which can provide exact guidelines for setting system parameters.Furthermore,by computing the rightmost characteristic root,the optimal parameter configuration for AVQ is derived,which can guarantee superior stability performance.Finally,some simulation examples are given to illustrate the correctness of the theoretical analysis.     

Generalized threshold replenishment: an adaptive vectorquantization algorithm for the coding of nonstationary sources

In this paper, we describe a new adaptive-vector-quantization (AVQ) algorithm designed for the coding of non-stationary sources. This new algorithm, generalized threshold replenishment (GTR), differs from prior AVQ algorithms in that it features an explicit, online consideration of both rate and distortion. Because of its online nature, GTR is more amenable to real-time hardware and software implementation than are many prior AVQ algorithms that rely on traditional batch training methods. Additionally, as rate-distortion cost criteria are used in both the determination of nearest-neighbor codewords and the decision to update the codebook, GTR achieves rate-distortion performance superior to that of other AVQ algorithms, particularly for low-rate coding. Results are presented that illustrate low-rate performance surpassing that of other AVQ algorithms for the coding of both an image sequence and an artificial non-stationary random process. For the image sequence, it is shown that (1) most AVQ algorithms achieve distortion much lower than that of nonadaptive VQ for the same rate (about 1.5 b/pixel), and (2) GTR achieves performance substantially superior to that of the other AVQ algorithms for low-rate coding, being the only algorithm to achieve a rate below 1.0 b/pixel.     

GA-BP神经网络在雷达目标跟踪中的应用研究

目标的运动过程一般是非线性过程,神经网络具有很强的非线性拟合能力,可映射任意复杂的非线性关系,以神经网络为基础的模型能够很好地反应目标的非线性运动趋势。本文在分析传统的BP神经网络的基础上,引入GA遗传算法来优化神经网络的初始权值和阀值,同时将GA-BP神经网络模型运用于对雷达目标的跟踪过程中,并通过仿真验证该模型的精度较高。     

IMPLEMENTING THE ADAPTIVE VECTOR QUANTIZER USING CARPENTER/GROSSBERG NET

AVQ(Adaptive Vector Quantizer)overcomes some shortcomings of traditional vectorquantizer with a fixed codebook trained and generated by the LBG or other algorithms by applyinga variab|e codebook.In this paper,we describe an effective and efficient implementation of AVQby modifying the CCN(Carpenter/Grossberg Net).The encoding process of AVQ is very similarto the learning process of the CGN.We study several different encoding schemes,includingwaveform AVQ,analysed parameter AVQ and so on,implemented by the CGN.And we simulatethe encoding performance of each scheme for encoding Gaussian process source,first order Gauss-Markov process source and practical speech signal.Our simulation results show that good qualityboth in subjective and objective tests can be obtained in a low or middle bit rate range.     

倾角传感器的小波阈值消噪

针对非平稳信号进行小波阈值消噪方法,提出了一种将广义交叉确认（GCV）规则和遗传算法结合的新方法,利用这种方法,可以求得近似最佳阈值。接着,将方法应用到倾角传感器信号消噪中,取得到了很好的效果。     

Multichannel ECG compression using multichannel adaptive vector quantization

Adaptive vector quantization (AVQ) is a recently proposed approach for electrocardiogram (ECG) compression. The adaptability of the approach can be used to control the quality of reconstructed signals. However, like most of other ECG compression methods, AVQ only deals with the single-channel ECG, and for the multichannel (MC) ECG, coding ECG signals on a channel by channel basis is not efficient, because the correlation across channels is not exploited. To exploit this correlation, an MC version of AVQ is proposed. In the proposed approach, the AVQ index from each channel is collected to form a new input vector. The vector is then vector quantized adaptively using one additional codebook called index codebook. Both the MIT/BIH database and a clinical Holter database are tested. The experimental results show that, for exactly the same quality of reconstructed signals, the MC-AVQ performs better than single-channel AVQ in terms of bit rate. A theoretical analysis supporting this result is also demonstrated in this paper. For the same and relatively good visual quality, the average compressed data rate/channel is reduced from 293.5 b/s using the single-channel AVQ to 238.2 b/s using the MC-AVQ in the MIT/BIH case.     

ITBES：一种基于门限与身份的WSN加密签名方法

为了提高基于身份的加密签名（IBES）系统中密钥生成中心（PKG）的可信性,采用门限密码学中的（t,n）秘密共享方法,对Xavier IBES算法进行了改进,将主密钥s共享于n个对等的可信第三方PKG之间,并且将改进后的新的基于门限与身份的加密签名一体化方法（ITBES）应用于无线传感器网络,从方法的复杂性、存储需求、安全性方面进行了分析,结果表明我们的方法能够提高PKG可信性,加强无线传感器网络的安全。     

Adaptive vector quantization with codebook updating based on locality and history

We propose two techniques that are applicable to any adaptive vector quantization (AVQ) systems. The first one is called the locality-based codebook updating: when performing a codebook updating, we update the operational codebook using not only the current input vector but also the codewords at all positions within a selected neighboring area (called the locality), while the operational codebook is organized in a "cache" manner. This technique is rationalized by the high correlation cross neighboring vectors that facilitates a more efficient coding of the indices of the codewords chosen from the codebook. The second technique is called the history aid, which makes use of the information of previously coded vectors to quantize the current input vector if it is used to update the operational codebook. A more effective AVQ system is obtained by combining together the history aid and the locality-based updating. Extensive simulations are carried out to demonstrate the improved results achieved by our AVQ systems. Particularly, when the operational codebook size is relatively small, the improvement over a benchmark AVQ system - the generalized threshold replenishment (GTR) - is drastic. For example, when the size is 32, testing on a nonstationary signal (containing frames from different video sequences, ordered in the concatenating or interleaving format) shows that the combination of history aid and locality-based updating offers more than 4 dB gain over GTR at 0.5 bpp.