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HNS: A streamlined hybrid network simulator

机译：HNS：简化的混合网络模拟器

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This article was motivated by the need to speed up complex network simulation, especially in telecommunications settings, where high bandwidth translates into exorbitant numbers of packets that take inordinate CPU time to simulate. Since the simulation complexity of fluid workload is invariant under bandwidth scaling, flows of discrete units of workload may be replaced by (approximate) fluid streams for savings in CPU time and memory storage.To this end, the article outlines the design of a new hybrid Java simulator, called HNS (Hybrid Network Simulator). HNS simulates the movement of workload in a queueing network, where transactions may be of two types: traditional discrete transactions (e.g., packets) and continuous (fluid) transactions, all of which arrive discretely at the network in traffic flows, and each discrete arrival carries a workload. Arriving transactions only differ in the way their workloads are transported: the user specifies whether the workload should be packetized or fluidized, respectively, for transport across the network. The novel feature of HNS is that it admits models with both discrete and continuous traffic flows, and collects detailed statistics for both, including arrival, loss, buffer contents, departure, and delay statistics. HNS facilitates the fundamental tradeoff between the modeling accuracy of discrete flows and savings in simulation time and storage often afforded by continuous flows by providing a common testbed for both discrete and continuous flows, where the user can readily select transport modes and achieve a good deal of variance reduction in assessing the accuracy and speeds of model versions with different mixtures of flow types. We caution, however, that while HNS is a generic hybrid simulator of discrete and continuous flows, mixed models should be handled with care, since they tend to counteract the advantages of pure-packet or pure-fluid models.In order to achieve a high degree of speedup for fluid-flow models, HNS introduces and utilizes the so-called streamlining methodology to identify and modify algorithms that cause "turbulent" fluid flow (namely, scenarios where fluid-flow rates have a large number of minor fluctuations, which are computationally expensive but have a minor impact on simulation statistics). Streamlining removes these fluctuations so as to speed up the simulation at a moderate loss of statistical accuracy. HNS can be extended by writing additional Java classes; in particular, stream behavior can be modified by extending built-in protocol classes. For example, HNS already has dual implementations (packet and fluid) of various telecommunications-specific protocols, such as ATM (Asynchronous Transfer Mode), User Datagram Protocol (UDP), and TCP (Transport Control Protocol), the latter with a streamlined fluid protocol approximation.In this article, we describe the architecture of HNS and its operational features, including traffic injection at network sources, generic workload transport, some telecommunications-specific protocols, and statistics collection and display via a graphic user interface (GUI). We then use HNS to validate the streamlining methodology and to study appropriate tradeoffs of simulation speed and accuracy in telecommunications networks by comparing pure-packet, pure-fluid, and mixed versions of the same network model.
机译：本文的动机是需要加快复杂的网络仿真速度，尤其是在电信设置中，在这种情况下，高带宽会转化为大量的数据包，而这需要大量的CPU时间来进行仿真。由于流体工作负载的模拟复杂度在带宽扩展下是不变的，因此可以用（近似）流体流代替离散工作负载单元的流，以节省CPU时间和内存存储。为此，本文概述了一种新的混合驱动程序的设计Java模拟器，称为HNS（混合网络模拟器）。 HNS在排队网络中模拟工作负载的移动，其中事务可能有两种类型：传统的离散事务（例如，数据包）和连续（流体）事务，它们均以流量的形式离散到达网络，并且每个离散到达承担工作量。到达的事务仅在其工作负载的传输方式上有所不同：用户指定应分别打包工作负载还是对工作负载进行打包以便在网络上传输。 HNS的新颖之处在于，它可以接受具有离散流量和连续流量的模型，并为这两种模型收集详细的统计信息，包括到达，丢失，缓冲区内容，离开和延迟统计信息。 HNS通过为离散流和连续流提供通用的测试平台，促进了离散流的建模精度与节省仿真时间和连续存储经常提供的存储之间的基本权衡，用户可以在其中轻松选择运输方式并实现很多在评估具有不同流类型混合的模型版本的准确性和速度时的方差减少。但是我们要注意的是，尽管HNS是离散和连续流的通用混合模拟器，但是应谨慎处理混合模型，因为它们往往会抵消纯数据包或纯流体模型的优势。为了提高流体流动模型的加速程度，HNS引入并利用了所谓的流线型方法来识别和修改导致“湍流”流体流动的算法（即，流体流动速率具有大量微小波动的场景，计算量大，但对模拟统计量影响较小）。精简消除了这些波动，从而在不影响统计准确性的情况下加快了仿真速度。可以通过编写其他Java类来扩展HNS。特别是，可以通过扩展内置协议类来修改流行为。例如，HNS已经具有各种电信特定协议的双重实现（数据包和流体），例如ATM（异步传输模式），用户数据报协议（UDP）和TCP（传输控制协议），后者具有简化的流体协议近似。在本文中，我们描述了HNS的体系结构及其操作功能，包括在网络源进行流量注入，通用工作负载传输，某些电信特定协议以及通过图形用户界面（GUI）进行统计信息收集和显示。然后，我们通过比较同一网络模型的纯数据包，纯流体和混合版本，使用HNS来验证简化方法并研究电信网络中仿真速度和准确性的适当折衷。

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