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Hua Long

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  1. Simulation of communication system Hua Long

  2. Chapter 1 Simulation Review

  3. Chapter 1 Simulation Review • $1.1What is Simulation ? • $1.2 Why do we need Simulation? • $1.3How many kinds of Classifying simulations?

  4. $1.1What is Simulation • Simulation is one of the most powerful analysis tools available to those responsible for the design and/or operation of complex processes or systems. • It is heavily based upon computer science, mathematics, probability theory and statistics: yet the process of simulation modeling and experimentation remains very much an intuitive art.

  5. $1.1What is Simulation • Simulation is defined: “the process of designing a computerized model of a system (or process) and conducting experiments with this model for the purpose either of understanding the behavior of the system and/or of evaluating various strategies for the operation of the system.” • The process of simulation to include both the construction of the model and the analytical use of the model for studying a problem

  6. $1.2 Why do we need Simulation 1.Performance evaluation Performance evaluation aims at forecasting system behaviors in a quantitative way. When-ever new systems are to be built or existing systems have to be reconfigured or adapted, performance evaluation can be employed to predict the impact of architectural or implementation changes on the system performance.

  7. $1.2 Why do we need Simulation An important aspect of performance evaluation is performance measurement or monitoring. 1.By monitoring the timing of certain important events in a system, insight can be obtained in which system operations take most time, or which system components are heavily loaded and which are not.

  8. $1.2 Why do we need Simulation 2. performance measurement System will have to be changed slightly in order to perform the measurements, (For example, extra code might be required to generate time-stamps and to write event logs) these alterations themselves affect the system performance. This is especially the case when employing software monitoring, or hardware monitoring. Hybrid monitoring can also be employed

  9. $1.2 Why do we need Simulation A model is an abstract description—— based on (mathematically) well-defined concepts, of a system in terms of its components and their interactions, as well as its interactions with the environment. The environment part in the model describes how the system is being used, by other systems. Very often, this part of the model is called the system workload model. The process of designing models is called modeling.

  10. $1.2 Why do we need Simulation With simulation, we mimic the system behaviors, generally by executing an appropriate simulation program. When doing so, we take time stamps, tabulate events, etc. After having simulated for some time, we use the time stamps to derive statistical estimates of the measures of interest. • Simulation can get solution when analytical techniques do not exist to obtain model solutions.

  11. $1.3How many kinds of Classifying simulations • we will classify simulations according to two criteria: their state space and their time evolution.

  12. $1.3How many kinds of Classifying simulations • In continuous-event simulations, systems are studied in which the state continuously changes with time. these systems are physical processes that can be described by systems of differential equations with boundary conditions.

  13. $1.3How many kinds of Classifying simulations • In discrete-event simulations the state changes take place at discrete points in time. Again we can either take time as a continuous or as a discrete parameter. In a discrete-event system, the state will change over time. The cause of a state variable change is called an event. Very often the state changes themselves are also called events.

  14. $1.3How many kinds of Classifying simulations In discrete-event simulations we “‘jump” from event to event and it is the ordering of events and their relative timing we are interested in. In a simulation program we will therefore mimic all the events. By keeping track of all these events and their timing, we are able to derive measures such as the average inter-event time or the average time between specific pairs of events. These then form the basis for the computation of performance estimates.

  15. $1.3How many kinds of Classifying simulations In a time-based simulation (also often called synchronous simulation) the main control loop of the simulation controls the time progress in constant steps.

  16. $1.3How many kinds of Classifying simulations

  17. $1.3How many kinds of Classifying simulations • Event-based simulation In event-bused simulations it is just the other way around. We then deal with time steps of varying length such that there is always exactly one event in every time step. So, the simulation is controlled by the occurrence of “next events”

  18. $1.3How many kinds of Classifying simulations

  19. Chapter 2 Modeling Overview

  20. Modeling Overview • OPNET provides a comprehensive development environment supporting the modeling of communication networks and distributed systems. • Both behavior and performance of modeled systems can be analyzed by performing discrete event simulations. • The OPNET environment incorporates tools for all phases of a study, including model design, simulation, data collection, and data analysis.

  21. System Features(1) • OPNET is a vast software package with an extensive set of features designed to support general network modeling and to provide specific support for particular types of network simulation projects.

  22. System Features(2) • Object orientation—Systems specified in OPNET consist of objects, each with configurable sets of attributes. Objects belong to classes, which provide them with their characteristics in terms of behavior and capability.

  23. System Features(3) • Specialized in communication networks and information systems—OPNET provides many constructs relating to communications and information processing, providing high leverage for modeling of networks and distributed systems.

  24. System Features(4) • Hierarchical models—OPNET models are hierarchical, naturally paralleling the structure of actual communication networks. • Graphical specification—Wherever possible, models are entered via graphical editors. These editors provide an intuitive mapping from the modeled system to the OPNET model specification.

  25. System Features(5) • Flexibility to develop detailed custom models—OPNET provides a flexible,high-level programming language with extensive support for communications and distributed systems. This environment allows realistic modeling of all communications protocols, algorithms, and transmission technologies.

  26. System Features(6) • Automatic generation of simulations—Model specifications are compiled automatically into executable, efficient, discrete-event simulations implemented in the C programming language.

  27. System Features(7) • Integrated post-simulation analysis tools—Performance evaluation, and trade-off analysis require large volumes of simulation results to be interpreted. OPNET includes a sophisticated tool for graphical presentation and processing of simulation output.

  28. System Features(8) • Interactive analysis—All OPNET simulations automatically incorporate support for analysis via a sophisticated interactive debugger. • Animation—Simulation runs can be configured to automatically generate animations of the modeled system at various levels of detail and can include animation of statistics as they change over time.

  29. System Features(9) • Cosimulation—You can connect OPNET with one or more other simulators so that you can see how the models in those simulators interact with OPNET models. • Application program interface (API)—As an alternative to graphical specification, OPNET models and data files may be specified via a programmatic interface. This is useful for automatic generation of models or to allow OPNET to be tightly integrated with other tools.

  30. Typical Applications of OPNET(1) • Standards-based LAN and WAN performance modeling—detailed library models provide major local-area and wide-area network protocols. Configurable application models are also provided by the library, or new ones can be created.

  31. Typical Applications of OPNET(2) • Internetwork planning—hierarchical topology definitions allow arbitrarily deep nesting of subnetworks and nodes and large networks are efficiently modeled; scalable, stochastic, and/or deterministic models can be used to generate network traffic.

  32. Typical Applications of OPNET(3) • Research and development in communications architectures and protocols—OPNET allows specification of fully general logic and provides extensive support for communications.Finite state machines provide a natural representation for protocols.

  33. Typical Applications of OPNET(4) • Distributed sensor and control networks, on-board. Customized performance metrics can be computed and recorded, stochastic inputs can be used to drive the simulation model, and processes can dynamically monitor the state of objects in the system via formal interfaces provided by statistic wires.

  34. Typical Applications of OPNET(5) • Resource sizing—accurate, detailed modeling of a resource’s request-processing policies is required to provide precise estimates of its performance when subjected to peak demand. (for example, a packet switch’s processing delay can depend on the specific contents and type of each packet as well as its order of arrival).

  35. Typical Applications of OPNET(6) • Mobile packet radio networks—specific support for mobile nodes, including predefined or adaptive trajectories; predefined and fully customizable radio link models; geographical context provided by OPNET network specification environment. (requires the Wireless module)

  36. CHAPTER 3 OPNET Modeler的构架和仿真机制

  37. OPNET Modeler • OPNET Modeler is based on a series of hierarchical editors that directly parallel the structure of real networks, equipment, and protocols. • It’s the leading industry/academic standard for Simulations. With it we can design and study communication networks, devices, protocols, and applications with unmatched flexibility and scalability • OPNET Modeler consists of the hierarchical editors for • Network Modeler • Node Modeler • Process Modeler • Open Modeler

  38. 对象和模型 • 对象是具有定义完备接口且通过接口能访问其内部结构,具有相似功能但又互不相同的,能完成一定功能实体。 • 建立表示具体网络设备或表示其工作方式的模型时,包括建立其内部结构、性能和表现形式等信息的规范,这些规范的集合被称为模型。对象是模型的实例,依赖于模型又具有相对的独立性。

  39. PROCESS/NODE/PROJECT • 最下层的进程模型在模型建立的过程也建立起表示其性能、结构和协议参数的属性。进程模型以*.pr.c和C、C++及管道阶段等文件保存。 • 节点域中处理器和队列模块的process model属性是联系节点模块与进程模型关系的接口,通过该接口将已经建好的进程模型绑定在节点模块上,此时称该节点模块是进程模型的对象。 • 节点域把具有不同功能的多个节点模块利用包流线、统计线或逻辑线的通信方式相连构成能实现更完整功能的节点域模型,模型文件以*.nd.m格式存放。 • 网络域节点属性model是网络域与节点域模型之间关系的接口,通过该接口将已经建好的节点域模型绑定在节点上,此时称该节点是节点模型的对象。

  40. 属性 • 确定模型性质的值称为属性。属性是对模型特性的描述。 • 属性分为两类:一类被隐藏的,一类展示给用户。后者的作用一方面将选择对象的特性告诉用户,另一方面允许用户为实现某些应用进行属性的修改。每种属性提供信息的存储,并构成了对象的说明。 • 属性按嵌套程度分为简单属性和复合属性两种。 • 简单属性:属性仅包含一个元素,且属性不包含嵌套对象。 • 复合属性:属性中还嵌套嵌套对象,嵌套对象又拥有自身属性。 • 复合属性的嵌套可以是多层。

  41. 属性的分类与设置 属性按存储类型分为私有和公有两类。 • 私有属性:表示属性仅属于特定对象。 • 公有属性:表示属性属于几个对象,公有属性提供了属性的复用机制和集中管理属性的方式。 • 属性的设置 直接设置模型属性 属性提升配置

  42. 基于时间的仿真 • 仿真中仿真时间随事件的单调增加。在仿真轴上存在多个仿真事件。事件在时间轴上以点在表示,这意味着在事件执行时仿真时间是不变化的。

  43. OPNET的通信机制 • 基于包的通信机制: 包的概念来自于实际网络,它代表一种对象,可以被动态的创建、修改、检查、复制、发送、接收以及销毁。 • 包的通信包括两种方式: (1)包流方式:利用包流线将两个相互通信的节点连接在一起,事件间的触发机制通过核心函数进行。

  44. 包传递方式:第二种处理方式是没有包流线相连的数据传输。传输机制与包流方式相似,不同的源和目的模块没有包流线相连。二者真正不同是寻址方式的不同。在包流方式机制中,包流队列、源模块和目的模块属于同一个节点,而包传递方式是源模块和包流队列及目的模块分属于不同的节点。包传递方式:第二种处理方式是没有包流线相连的数据传输。传输机制与包流方式相似,不同的源和目的模块没有包流线相连。二者真正不同是寻址方式的不同。在包流方式机制中,包流队列、源模块和目的模块属于同一个节点,而包传递方式是源模块和包流队列及目的模块分属于不同的节点。

  45. 基于ICI通信机制 • Interface Control Information Structures(ICI)

  46. 物理层的仿真(1) • 管道阶段 物理链路有三种形式,即点到点、总线和无线。 点到点信道包含的特性: • 发送时延:发送模块发送第一个比特开始到最后一个比特结束时所需要的时间,这被称为发送时延。 • 传播时延:信号从源发送到信号到目的地存在的时延。 • 差错率:考虑链路内存在误码,模拟出错和纠错。 • 点到点链路管道阶段

  47. 物理层的仿真(2) • 总线信道包含的特性:除点到点的特性外,还包含冲突检测

  48. 物理层的仿真(3)-无线链路仿真

  49. Chapter 4 Projects Model

  50. Projects and Scenarios • ITDG uses a Project and Scenario approach to modeling networks. • A Project is a collection of related network scenarios that each explores a different aspect of network design. All projects contain at least one scenario. • A Scenario is a single instance of a network. Typically, a scenario presents a unique configuration for the network, where configuration refers to such aspects as topology, protocols, applications, baseline traffic, and simulation settings.