Modeling two-windows TCP behavior in differentiated services networks

Two important issues in assured services within differentiated services architecture are bandwidth guarantee and fair sharing of unsubscribed bandwidth among TCP flows with and without bandwidth reservations. Although the subscribed bandwidth can be guaranteed by increasing network capacity or deploying strict admission control mechanisms, the costs of such solutions are very high. The issue of fair sharing of excess bandwidth is also not well solved. To address those issues, a modified TCP, named two-windows TCP, has been proposed. The performance of the protocol is evaluated by simulations. But its effectiveness is not validated theoretically under general network conditions, which is important for understanding the benefits and costs of using the protocol. In this paper, an analytical model is developed for the purpose. The model characterizes throughput of individual two-windows TCP flow as a function of contract rate, round trip time, loss rates of In and Out packets. Extensive simulations validate the analytical model. It's shown two-windows TCP is effective not only on solving the issues of bandwidth guarantee and fair sharing of unsubscribed bandwidth, but also on increasing the utilization of bottleneck link bandwidth. Moreover, its performance is robust to network conditions, which is important for wide deployment over Internet.     

Adaptive hinging hyperplanes and its applications in dynamic system identification

The model of adaptive hinging hyperplanes (AHH) is proposed in this paper. It is based on multivariate adaptive regression splines (MARS) and generalized hinging hyperplanes (GHH) and shares attractive properties of the two. By making a modification to the basis function of MARS, AHH shows linear property in each subregion. The AHH model is actually a special case of the GHH model, which has a universal representation capability for continuous piecewise linear functions. The approximation ability of the AHH model is proved. The AHH algorithm is developed similar to the MARS algorithm. It is adaptive and can be executed efficiently, hence has power and flexibility to model unknown relationships. The AHH procedure is applied to identifying two dynamic systems and its potential is illustrated.     

Improving routing in long-distance wireless mesh networks via a distributed embedded router

The paper addresses some issues concerning routers for long-distance wireless mesh networks (LDWMNs) which are becoming increasingly popular in the last few years, above all to provide Internet access for small extra-urban communities. The paper discusses some main features of LDWMNs, the design challenges and the reasons behind the implementation choices. A router is described, based on a modular architecture which provides fault tolerance and guarantees gracefully degrading performances in case a fault occurs. One important feature of the router is the full-duplex capability of its wireless links which provides high throughput. Finally, the paper describes the implementation of the router using low-cost embedded components and addresses some issues concerning the management of the wireless links in the wireless mesh backbone.     

移动自组网中基于多约束和协同过滤动态信任机制*

由于具有分布式特性,导致移动自组网容易遭受攻击。为了增强移动自组网的安全性,建立一套适合自组织、无认证中心的节点信任评估模型是非常必要的。因此,提出了一种移动自组网中基于多约束和协同过滤的动态信任机制。其主要思想是在根据节点自身的经历的基础上,采用一个带多约束的信任更新算法来评估直接信任。其中：时间衰减因子保证了信任度随时间进行衰减;奖励因子保证了良好的节点应受到奖励;惩罚因子保证了恶意节点应受到惩罚。另外,采用协同过滤技术来评估推荐信任,以此来阻止不诚实的推荐。通过定量评估分析和模拟仿真,结果表明所提出的方法比Bayesian模型能更精确地计算节点之间的信任度和提高移动自组网的安全性。     

On “cheap smoothing” opportunities in identification of time-varying systems

In certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of “future” data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing algorithms are seldom used in practice, mainly because of their high computational requirements. We show that the computationally attractive smoothing procedures can be obtained by means of compensating estimation delays that arise in the standard exponentially weighted least squares, least mean squares and Kalman filter-based parameter trackers.     

Design and performance analysis of tracking controller for uncertain nonlinear composite system using neural networks

Based on high order dynamic neural network, this paper presents the tracking problem for uncertain nonlinear composite system, which contains external disturbance, whose nonlinearities are assumed to be unknown. A smooth controller is designed to guarantee a uniform ultimate boundedness property for the tracking error and all other signals in the dosed loop. Certain measures are utilized to test its performance. No a priori knowledge of an upper bound on the “optimal” weight and modeling error is required; the weights of neural networks are updated on-line. Numerical simulations performed on a simple example illustrate and clarify the approach.     

Adaptive pre-task assignment scheduling strategy for heterogeneous distributed raytracing system

One of the main obstacles in obtaining high performance from heterogeneous distributed computing (HDC) system is the inevitable communication overhead. This occurs when tasks executing on different computing nodes exchange data or the assigned sub-task size is very small. In this paper, we present adaptive pre-task assignment (APA) strategy for heterogeneous distributed raytracing system. In this strategy, the master assigns pre-task to the each node. The size of sub-task for each node is proportional to the node’s performance. One of the main features of this strategy is that it reduces the inter-processes communication, the cost overhead of the node’s idle time and load imbalance, which normally occurs in traditional runtime task scheduling (RTS) strategies. Performances of the RTS and APA strategies are evaluated on manager/master and workers model of HDC system. The experimental results of our proposed (APA) strategy have shown a significant improvement in the performance over RTS strategy.     

Adaptive routing in wormhole-switched necklace-cubes: Analytical modelling and performance comparison

The necklace hypercube has recently been introduced as an attractive alternative to the well-known hypercube. Previous research on this network topology has mainly focused on topological properties, VLSI and algorithmic aspects of this network. Several analytical models have been proposed in the literature for different interconnection networks, as the most cost-effective tools to evaluate the performance merits of such systems. This paper proposes an analytical performance model to predict message latency in wormhole-switched necklace hypercube interconnection networks with fully adaptive routing. The analysis focuses on a fully adaptive routing algorithm which has been shown to be the most effective for necklace hypercube networks. The results obtained from simulation experiments confirm that the proposed model exhibits a good accuracy under different operating conditions.     

Contention-based performance evaluation of multidimensional range search in peer-to-peer networks

Performance evaluation of peer-to-peer search techniques has hitherto been based on simple performance metrics, such as message hop counts and total network traffic, mostly disregarding the inherently concurrent nature of peer-to-peer networks, where contention may arise. This paper is concerned with quantifying the effects of contention in P2P networks, focusing on networks for multidimensional range search. We evaluate peer-to-peer networks derived from recently proposed works, introducing two novel metrics related to concurrency and contention, namely responsiveness and throughput. Our results highlight the impact of contention on these networks, and demonstrate that some studied networks do not scale in the presence of contention. Also, our results indicate that certain P2P network properties believed to be desirable (e.g. even data distribution or uniform peer access) may not be as critical as previously believed.     

自适应粒子滤波在卫星紫外导航中的应用

基于紫外敏感器的自主导航系统是典型的非线性和噪声非高斯分布的系统,针对扩展卡尔曼滤波(EKF)和Unscented 卡尔曼滤波(UKF)不适于噪声非高斯分布的系统,和一般粒子滤波缺乏在线自适应调整能力等问题,提出了将基于正交性原理的自适应强跟踪滤波器(STF)和UKF相融合作为重要密度函数,应用于基于紫外敏感器自主导航粒子滤波器新方法,通过UKF构造粒子群,对粒子群中的每一个粒子的每一个sigma点用STF进行更新,使得算法的鲁棒性增强,有极强的对突变状态的跟踪能力,具有强的自适应能力.为了说明算法的有效性,结合模拟的轨道数据和测量数据进行了仿真,仿真结果说明了所提算法的有效性.     

Adaptive searching and replication of images in mobile hierarchical peer-to-peer networks

Due to the limitation of resources in mobile handheld devices and bandwidth constraints in wireless networks, it is important to efficiently manage image content and traffic to improve network throughput and response time. The efficient distribution of images in wireless networks is based on many parameters like the quality of service requirement, available bandwidth, restricted memory and diverse user profiles. We consider digital images as data objects accessed in a hierarchical mobile ad-hoc peer-to-peer network, referred as M-P2P. Our objective is to optimize the number of replicas of images in such a network architecture based on the resource limitations of the requesting peers equipped with miniature mobile devices as well as of wireless constraints in mobile ad-hoc networks (MANET). While replicating images, fragments of different resolution and their residues are used to optimize the traffic in the network and to decrease the search turnaround time. We call this replication algorithm as Ada-Rep. Performance evaluation is done by simulating Ada-Rep, base replication and uniform replication methods to evaluate parameters such as response time, failure rate, memory usage, traffic etc. Our results prove the efficiency and better performance of Ada-Rep.     

On using least-squares updates without regressor filtering in identification and adaptive control of nonlinear systems

In continuous-time system identification and adaptive control the least-squares parameter estimation algorithm has always been used with regressor filtering, which adds to the dynamic order of the identifier and affects its performance. We present an approach for designing a least-squares estimator that uses an unfiltered regressor. We also consider a problem of adaptive nonlinear control and present the first least-squares-based adaptive nonlinear control design that yields a complete Lyapunov function. The design is presented for linearly parametrized nonlinear control systems in ‘normal form’. A scalar linear example is included which adds insight into the key ideas of our approach and allows showing that, for linear systems, our Lyapunov-LS design with unfiltered regressor, presented in the note for unnormalized least-squares, can also be extended to normalized least-squares.     

Evaluation of the Force Sensitive Application hand force measurement system

The Force Sensitive Application (FSA) system is used to measure forces exerted by the hand on an object. The present study evaluated the FSA system in terms of stability, repeatability, accuracy, and linearity at the sensor and system (pulp press, pulp pinch, and power grip) levels. At the sensor level, the FSA sensor showed high performance in stability (coefficient of variation [CV] ≤2%) and linearity (coefficient of determination [R²] = 0.95), but low performance in repeatability (CV = 11∼19%) and accuracy (14∼26% overvaluation). At the system level, the FSA system showed a decreasing accuracy (12∼30% undervaluation) as the number of sensors involved in the test increased, but retained a high linearity (R² = 0.95∼0.98) to measurement from a dynamometer. These evaluation results indicate that the FSA system should be used for relative, not absolute, comparison in force evaluation due to its lack of accuracy and that the accuracy of the FSA system can be improved due to its good linearity by calibrating FSA measurements with a dynamometer having a high level of accuracy. © 2010 Wiley Periodicals, Inc.     

Performance evaluation of TCP connections in ideal and non-ideal network environments

In this paper, we study the performance of TCP in both ideal and non-ideal network environments. For the ideal environments, we develop a simple analytical model for the throughput and transfer time of TCP as a function of the file size and TCP parameters. Our simulation measurements demonstrate that this model can accurately predict the throughput for ideal TCP connections characterized by no packet loss due to congestion or bit errors. If these ideal conditions are not met, the model gives an upper bound for throughput and lower bound for transfer time. For the non-ideal environments, we concentrate on wireless links. While our ideal model provides an easy to use tool to calculate bounds on the performance of all TCP implementations in such environments, we also show through simulation the relative performance of four well-known TCP implementations. We also present simulation results that demonstrate the dominant factors affecting the performance of wireless TCP.     

无线网络中自适应调制编码联合ARQ的性能分析

自适应调制编码(AMC)利用无线信道衰落的特点,灵活调整发射速率,能有效提高带宽资源的利用率.自动要求重传(ARQ)利用错误重传来提高传输的可靠性.对自适应调制编码联合自动要求重传这一典型跨层设计问题进行了性能分析,分析了队头分组的发送过程,数学推导了队头分组的传输时间及其概率分布和平均传输时间.最后,研究了平均信噪比和多普勒频率对传输时间的影响.     

神经网络与DE算法在自适应滤波中的应用

为了满足电流互感器自动测试系统中处理采集数据的需求,提出了一种基于神经网络与微分进化算法的自适应滤波器.在传统自适应滤波器结构中引入神经网络,提高了非线性处理能力;而微分进化算法则能保证全局最优解.试验表明,将改进后的滤波器应用于测试系统中具有较好的滤波效果,验证了该滤波方法应用于工业测控领域的正确性与可行性.     

Adaptive wormhole routing in tori with faults: A mathematical approach

Fault-tolerance in a communication network is defined as the ability of the network to effectively utilize its redundancy in the presence of faulty components (i.e., nodes or links). New technologies of integration now enable the design of computing systems with hundreds and even thousands of independent processing elements which can cooperate on the solution of the same problem for a corresponding improvement in the execution time. However, as the number of processing units increases, concerns for reliability and continued operation of the system in the presence of failures must be addressed. Adaptive routing algorithms have been frequently suggested as a means of improving communication performance in large-scale massively parallel computers, Multiprocessors System-on-Chip (MP-SoCs), and peer-to-peer communication networks. Before such schemes can be successfully incorporated in networks, it is necessary to have a clear understanding of the factors which affect their performance potential. This paper proposes a novel analytical model to investigate the performance of five prominent adaptive routings in wormhole-switched 2-D tori fortified with an effective scheme suggested by Chalasani and Boppana [S. Chalasani, R.V. Boppana, Adaptive wormhole routing in tori with faults, IEE Proc. Comput. Digit. Tech. 42(6) (1995) 386–394], as an instance of a fault-tolerant method widely used in the literature to achieve high adaptivity and support inter-processor communications in parallel computers. Analytical approximations of the model are confirmed by comparing them with those obtained through simulation experiments.     

前向纠错编码在网络传输协议中的应用综述

前向纠错编码是一种在网络传输中应对丢包的技术.在传输过程中加入冗余数据,使接收端在丢包场景下可通过冗余数据直接恢复出原始数据.在丢包多、时延大的场景下,适当加入前向纠错编码可以大量节省超时重传的等待时间,从而提高网络传输的服务质量.过多地添加冗余会造成带宽的浪费,而过少地添加冗余会导致服务器端接收到的数据不足以恢复在传...     

自适应混合滤波在脉搏实时监测系统中的应用

针对脉搏传感器在数据采集过程中干扰信号对系统测量精度带来的影响,提出了一种自适应混合滤波算法.该算法将限幅滤波、递推中位值平均滤波、递推平均滤波相结合,并针对采样长度对滤波效果的影响,自适应采样窗口大小的调整,可有效消除偶然脉冲与抑制周期性脉冲的干扰.通过对10名测试者进行测量实验,将心电图机测量数据、使用与未使用自适应混合滤波的脉搏实时监测系统测量数据进行对比.实验结果表明:使用滤波算法后,脉搏测量的算术平均差约为0.4 BPM,比未使用滤波算法整体提高约9倍.     

无线传感器网络环境下基于粒子滤波的移动机器人SLAM算法

定位问题是移动机器人研究领域中最基本的问题,在Bayes的框架下研究了机器人与无线传感器网络(WSN)组成系统中的同时建图与定位问题(SLAM).针对该系统中只存在距离测量信息可用的情况提出了一种基于粒子滤波的SLAM算法.该方法将机器人状态和节点位置估计设置为一组全局估计粒子,通过对粒子及其权重的更新来计算整个系统的状态.算法将WSN节点的位置估计在机器人的路径上分解为相互独立的估计,从而将全局粒子的计算转化为使用一个机器人状态滤波器和对应于每个机器人粒子的节点位置滤波器进行计算.针对观测信息低维的特点,设计了处理低维观测信息的方法,使得观测信息可以在滤波阶段得到合理利用.并且详细介绍了提出的SLAM算法原理和计算过程,并通过仿真实验证明了算法的有效性和实用性.