Enabling network calculus-based simulation for TCP congestion control

In this paper, we propose to speed up the simulation performance for TCP-operated networks by incorporating network calculus-based models in a simulation framework. In the simulation framework, we describes the operational properties of TCP congestion control, additive increase and multiplicative decrease (AIMD) and slow start, together with the queue discipline in the domain of network calculus. In order to determine network calculus models for TCP congestion, we first devise a simple TCP throughput model which approximately determines the range of per-flow throughput that one TCP can attain in a given interval, given the number of packet losses in the interval. We then exploit the TCP model to define a collection of network calculus theorems that regulate TCP flows in the range between the upper- and lower-limits on the TCP per-flow throughput in the corresponding interval. Finally, we incorporate the derived rules (theorems) into ns-2 to obtain a network calculus-based (NC-based) simulation, and carry out both the NC-based and the packet-level simulation to evaluate the performance gain and accuracy of the NC-based simulation, where the former is represented in perspective of the execution time (wall time) incurred in conducting the simulations and the later is evaluated in terms of the difference between results obtained in both the packet-level and NC-based simulation. The simulation results indicate that an order of magnitude or more (maximally 30 times) improvement in the execution time is achieved and the performance improvement becomes more salient as the network size increases in perspective of network-link capacities and the number of flows. The discrepancy observed between the NC-based simulation and the packet-level simulation, on the other hand, is minimally 1–2% and maximally 8–12% in a wide spectrum of network topologies and traffic loads. Additionally the results also indicate that the NC-based simulation outperforms a fluid-model-based simulation realized with the use of the time-stepped hybrid simulation technique, and that the performance improvement of the NC-based simulation is still held in IEEE 802.11-based wireless networks and also immune to the type of the simulation platform consisting of ns-2, operating system, and hardware specification.     

Reliability consideration of a mobile communication system with network congestion

High quality traffic for networks is urgently needed for mobile communication systems. Mobile stations frequently become unavailable due to communication errors generated by network congestion. Traffic congestion in a network system may occur intermittently and continue for a length of time, sometimes causing communication errors. If congestions happens during communication, communication errors occur and the communication is rejected. This paper considers the problem of reliability in mobile communication systems during congestion by using a recovery scheme. We formulate a stochastic model of a mobile communication system which consists of mobile stations, several base stations and a switching center. When communication errors occur, the system makes a rollback recovery and returns to the recent checkpoint. We derive the mean time to take checkpoint and the expected number of rollback recoveries, handoff, and successful transmissions until communication errors occur. Further, we calculate the expected costs and discuss ways to minimize the costs by analyzing the optimal checkpoint intervals.     

应用MTLAB分析模拟化学振荡的过程

化学振荡反应作为非线性科学研究的真实典型范例,采用传统的计算机语言编程,作理论分析模拟烦琐而困难。本文建议用MATLAB功能强大的solve,jacobian,eig,ode,plot等内部函数,对Lotka-Volterra和Belousov-Zhabotinsky两个典型的化学振荡反应进行理论分析和数值模拟。结果表明MATLAB能够可靠、简便地寻找出振荡动力学区域并对化学动力学方程组数值积分,可以成为化学振荡理论研究的有力工具。     

基于Agent的森林火灾系统建模仿真

为研究森林火灾系统的整体发展态势及演化规律,引入面向模式的基于Agent的建模方法,进行了融合自然、社会微观作用机理的计算机仿真研究,以Agent元模型为软件实现基础建立起森林火灾系统模型,有机融合了林火蔓延的元胞自动机模式和协作扑救的网络协作模式.对森林火灾系统模型进行动态仿真实验,实验结果表明了有关模式对系统态势发展的影响,以及基于Agent的建模方法对森林火灾系统研究的有效性.     

Pricing and congestion management in a network with heterogeneous users

This note presents an economic model for a communication network with utility-maximizing elastic users who adapt to congestion by adjusting their flows. Users are heterogeneous with respect to both the utility they attach to different levels of flow and their sensitivity to delay. Following Kelly et al. (1998), we introduce dynamic rate-control algorithms, based on the users' utility functions and delay sensitivities, as well as tolls charged by the system, and examine the behavior of these algorithms. We show that allowing heterogeneity with respect to delay sensitivity introduces a fundamental nonconvexity into the congestion-cost functions. As a result, there are often multiple stationary points of the aggregate net utility function. Hence, marginal-cost pricing-equating users' marginal utilities to their marginal costs-may identify a local maximum or even a saddle point, rather than a global maximum. Moreover, the dynamic rate-control algorithm may converge to a local rather than global maximum, depending on the starting point. We present examples with different user utility functions, including some in which the only interior stationary point is a saddlepoint which is dominated by all the single-user optimal allocations. We also consider variants of the dynamic algorithm and their performance in a network with heterogeneous users. Our results suggest that applying a rate-control algorithm such as TCP (Transmission Control Protocol), even when augmented by some form of implicit or explicit pricing, may have unexpected and perhaps undesirable effects on the allocation of flows among heterogeneous delay-sensitive users.     

新型伺服控制系统的建模仿真与分析

分析了伺服控制系统的工作原理,提出一种新型伺服控制系统建模方法。在Matlab/Simulink环境下采用模块化的方法构建了系统的仿真模型,系统采用双闭环控制,并对该模型进行了仿真。仿真结果表明,该系统具有良好的动态和静态特性,验证了该方法的有效性,为实际伺服控制系统的设计和调速提供了新的方法。     

Ontology based web simulation system for hydrodynamic modeling

Hydrodynamic models generally deal with large sets of data and utilize substantial computational resources. Powerful, robust servers with extensive storage capabilities are desirable for rapid execution. Unfortunately, it is not always possible to effort those kinds of facilities whereas a centralized computer system together with a user access interface can be a viable alternative for many clients. The simplest way a client can communicate with the central simulation server is by a web browser because it is available as a pre-installed application on most every computing platform purchased today. This type of environment is called web based simulation or WBS. In this study, the concepts necessary to design and develop a WBS for the simulation of hydrodynamic processes using legacy (FORTRAN) code are introduced. A formal specification of the simulation domain or an ontology has been developed that is the underlying concept to share, retrieve, and move the simulation data between the different components of the WBS. This ontology can also be used for future analysis and reuse of the simulation domain concepts and the associated data sets.     

Agent-based modeling and simulation of an autonomic manufacturing execution system

Production management systems must constantly deal with unplanned disruptive events and disturbances such as arrivals of rush orders, raw material shortage/delays or equipment breakdowns along with a multitude of interactions in the supply chain which constantly demand on-line task rescheduling and order execution control. For responsiveness and agility at the shop-floor, a distributed design for manufacturing execution systems is proposed based on autonomic units that fill the gap between production planning and shop-floor control. An interaction mechanism designed around the concept of order and resource agents implementing the monitor-analyze-plan-execution loop is described. Generative simulation modeling of an autonomic manufacturing execution system (@MES) is proposed in order to evaluate emerging behaviors and macroscopic dynamics in a multiproduct batch plant. Results obtained for an industrial case study using a simulation model of the proposed @MES are presented. The usefulness of agent-based modeling and simulation as a tool for distributed MESs design and to verify performance, stability and disturbance rejection capability of an interaction mechanism is highlighted.     

车载组合导航定位系统误差建模及仿真

首先,建立测速仪与惯性测量单元的组合导航状态方程、量测方程和车栽组合导航定位系统的卡尔曼滤波误差模型;其次,根据车载导航数据,进行了卡尔曼滤波仿真分析,评估了测速仪、惯性测量单元组合精度对导航定位精度的影响,结果表明了该方法的有效性.     

离散制造系统规划与仿真建模研究

对离散制造过程的规划、建模和仿真技术进行了研究,建立了面向对象的系统模型,分析了仿真运行机理,通过仿真分析优化生产制造系统性能指标。应用实例,介绍了基于eM—Plant环境进行生产线建模仿真、设备布局、瓶颈分析的过程,为离散制造过程研究提供了有效的方法。     

Simulation of a production line system with machine breakdowns using network modeling

In a manufacturing system, several factors can affect the reliability of the system in producing expected output levels, including resource input rates, labor rate variability, product quality, and machine failures. Although all of these factors will be reflected in the modeling process presented in this paper, the primary focus will be on the effect of machine breakdowns on system output. Network modeling and simulation with Q-GERT is the vehicle of analysis that is employed. This technique will be demonstrated via a realistic case example encompassing a complex production system consisting of several assembly lines, each containing several machines. The statistical results of the simulation of the example system are presented and discussed. In addition, examples of how the simulation model can be used to test changes in machine repair times and breakdown rates will be presented.     

无线通信系统的Petri网建模与分析

无线通信系统是一个分布式实时多任务数据处理系统,具有实时性、并发、异步和多任务等特点.Petri网是描述和分析异步并发现象的一种有效的模型工具.以Petri网为工具,建立了无线通信系统的仿真模型,对其功能和数据流进行模拟,并对其结构性能、任务的忙闲程度、死锁进行了定性分析,实现了模型和程序结构的自动转换,从一个全新角度对无线通信系统进行了分析和评价.     

Process modeling with the regression network

A new connectionist network topology called the regression network is proposed. The structural and underlying mathematical features of the regression network are investigated. Emphasis is placed on the intricacies of the optimization process for the regression network and some measures to alleviate these difficulties of optimization are proposed and investigated. The ability of the regression network algorithm to perform either nonparametric or parametric optimization, as well as a combination of both, is also highlighted. It is further shown how the regression network can be used to model systems which are poorly understood on the basis of sparse data. A semi-empirical regression network model is developed for a metallurgical processing operation (a hydrocyclone classifier) by building mechanistic knowledge into the connectionist structure of the regression network model. Poorly understood aspects of the process are provided for by use of nonparametric regions within the structure of the semi-empirical connectionist model. The performance of the regression network model is compared to the corresponding generalization performance results obtained by some other nonparametric regression techniques.     

Integrated evolutionary neural network approach with distributed computing for congestion management

Electric supply industry is facing deregulation all over the world. Under deregulated power supply scenario, power transmission congestion has become more intensified and recurrent, as compared to conventional regulated power system. Congestion may lead to violation of voltage or transmission capacity limits, thus threatens the power system security and reliability. Also the growing congestion may lead to unanticipated divergent electricity pricing. Owing to these facts congestion management has become a crucial issue in the deregulated power system scenario.Fast and precise prediction of nodal congestion prices in real time deregulated/spot power market may enable market participants and system operators to keep pace with the congestion by taking preventive measures like transaction rescheduling, bids (both for supplying and consuming electricity) modification, regulated dispatch of electric power, etc. This paper proposes an integrated evolutionary neural network (ENN) approach to predict nodal congestion prices (NCPs) for congestion management in spot power market. Distributed computing is employed to tackle the heterogeneity of the data in the prediction of NCP values. Developed ENNs have been trained and tested under distributed computing environment, using a message passing paradigm. Proposed hybrid approach for NCP prediction is demonstrated on a 6-bus test power system with and without distributed computing. The proposed approach not only demonstrated the computing efficiency of the developed ENN model over the conventional optimal power flow method but also shows the time saving aspect of distributed computing.     

Stroke-based modeling and haptic skill display for Chinese calligraphy simulation system

The goal of this paper is to study haptic skill representation and display in a Chinese calligraphy training system. The challenge is to model haptic skill during the writing of different strokes in Chinese characters and to achieve haptic rendering with high fidelity and stability. The planning of the writing process is organized at three levels: task, representation and device level to describe the haptic handwriting skill. State transition graph (STG) is proposed to describe switches between tasks during the handwriting. Chinese characters are modeled using 39 typical strokes, which are further grouped into basic and compound strokes. The compound stroke is considered to be sequential combination of the basic strokes. Straight and curve strokes are modeled using line segment and the Bezier curve, respectively. Information from STG is used for real-time collision detection and haptic rendering. Ambiguity of the collision detection at stroke-corner points is prevented using active stroke combined with local nearest point computation. A modified virtual fixture method is developed for haptic rendering. The approach is tested on a prototype training system using Phantom desktop. Initial experiments suggest that the proposed modeling and rendering method is effective.     

A network rate management protocol with TCP congestion control and fairness for all

Our study is motivated by the need to enable quality of service (QoS), congestion control and fair rate allocation for all end applications. We propose a new approach to address these needs which is different from the current practice whereby end applications pursue their own rate control using TCP. Our approach comprises a network rate management protocol (RMP) that controls the rate of all flows (at an aggregate level based on routes) subject to QoS requirements. The RMP control also facilitates a new TCP sliding-window congestion control based on the fair target rates computed by the RMP. Each non-TCP aggregate flow is policed by its respective edge router and each TCP flow adapts its window size as to achieve the RMP suggested fair target rate. The stability analysis of the new TCP congestion control is performed in a linearly scalable framework, which is less restrictive than a fluid model. We show that our proposed control is linearly scalable and establish its global asymptotic stability under arbitrary and variable information time lags, aka totally asynchronous conditions. The stability and the vitality of our control is verified by two means. One is a simulation of a network comprising 74 core links and up to 768 flows, each using its own access link. The simulation is also used to compare our control with the congestion control algorithms used in Fast, Vegas and Reno TCPs. The second verification means is an actual implementation of the control in the Linux kernel and its experimentation in a WAN testbed network comprising six routers and long haul links running UDP flows as well as CUBIC, N-RENO and C-TCP flows. Our experiments demonstrate that our approach can guarantee fair rates for all flows and QoS to premium flows.     

基于Agent能源基础设施仿真模型设计与实现

建模仿真可以有效模拟能源基础设施在危机态下的行为特点以及对社会的影响.设计了包含电力、石油和天然气管网三种类型的能源基础设施模型;详细介绍了能源基础设施模型的结构设计,以及模型内各类主体Agent的结构、功能、通信方式和行为规则的设计;通过对能源基础设施运行特点和限制条件的分析,在模型中确定并应用能源运动稳态算法,并设计了模型可视化系统.     

应用网络数据通信的飞行模拟系统

介绍了一种应用网络进行数据通信的飞行模拟系统，由于本系统实时性要求强，在两站之间使对等通讯，阐述了应用网间数据包交换协议进行网络数据通信的通信过程，实现了目标投影系统和天地景系统的要求功能，获得满意的控制效果。     

网络仿真协作实验系统应用模型研究

随着网络技术的高速发展,网络教育在现代教育中所占地位越来越重要;其次,协作学习也以其众多的优势越来越受到广大教育工作者的重视。但是对于在工程学科中占有重要地位的实验环节,目前的网络教育课程还提供得很少。本文介绍了协作学习的概念和优点,并将其应用到网络教育和工程实验中,引入了网络仿真协作实验的概念,分析了网络协作实验系统的发展现状,描述了网络仿真协作实验系统的结构;设计了网络协作实验系统的应用模型,研究了这一模型中的主要技术,最后将该模型应用到多元精馏实验系统中,实现了多元精馏仿真协作实验系统。     

基于感知器算法的网络拥塞控制研究

对基于TCP协议的拥塞控制局限性和常见的拥塞控制算法进行分析,提出了一种全局性的拥塞控制策略处理新方法.通过网络监控软件获取网络设备的端口参数信息,利用神经元网络单层感知器学习算法检测网络拥塞发生,记忆当前网络状态的参数,再判断新输入模式是否导致拥塞发生,进而修改参数并避免网络拥塞.MATLAB仿真结果表明,使用这种神经元网络模型能够对网络拥塞进行有效地控制,提高网络传输性能.