首页> 外文学位 >High performance simulation of DEVS based large scale cellular space models.
【24h】

High performance simulation of DEVS based large scale cellular space models.

机译:基于DEVS的大规模蜂窝空间模型的高性能仿真。

获取原文
获取原文并翻译 | 示例

摘要

Cellular space modeling is becoming an increasingly important modeling paradigm for modeling complex systems with spatial-temporal behaviors. The growing demand for cellular space models has directed researchers to use different modeling formalisms, among which Discrete Event System Specification (DEVS) is widely used due to its formal modeling and simulation framework. The increasing complexity of systems to be modeled asks for cellular space models with large number of cells for modeling the systems' spatial-temporal behavior. Improving simulation performance becomes crucial for simulating large scale cellular space models.;In this dissertation, we proposed a framework for improving simulation performance for large scale DEVS-based cellular space models. The framework has a layered structure, which includes modeling, simulation, and network layers corresponding to the DEVS-based modeling and simulation architecture. Based on this framework, we developed methods at each layer to overcome performance issues for simulating large scale cellular space models. Specifically, to increase the runtime and memory efficiency for simulating large number of cells, we applied Dynamic Structure DEVS (DSDEVS) to cellular space modeling and carried out comprehensive performance measurement. DSDEVS improves simulation performance by making the simulation focus only on those active models, and thus be more efficient than when the entire cellular space is loaded. To reduce the number of simulation cycles caused by extensive message passing among cells, we developed a pre-schedule modeling approach that exploits the model behavior for improving simulation performance. At the network layer, we developed a modified time-warp algorithm that supports parallel simulation of DEVS-based cellular space models. The developed methods have been applied to large scale wildfire spread simulations based on the DEVS-FIRE simulation environment and have achieved significant performance results.;INDEX WORDS: DEVS, High performance, Cellular space, Dynamic structure, Modeling and simulation, Time warp optimistic, Parallel and distributed computing.
机译:蜂窝空间建模正成为用于建模具有时空行为的复杂系统的越来越重要的建模范例。对蜂窝空间模型的日益增长的需求已指导研究人员使用不同的建模形式,其中离散事件系统规范(DEVS)因其形式化的建模和仿真框架而被广泛使用。要建模的系统的复杂性不断提高,需要具有大量单元的蜂窝空间模型来对系统的时空行为进行建模。提高仿真性能对于仿真大规模蜂窝空间模型至关重要。本文为基于DEVS的大规模蜂窝空间模型提出了一种提高仿真性能的框架。该框架具有分层的结构,其中包括建模,仿真和与基于DEVS的建模和仿真架构相对应的网络层。在此框架的基础上,我们在每一层开发了方法来克服模拟大型蜂窝空间模型的性能问题。具体来说,为了提高运行时间和内存效率以模拟大量单元,我们将动态结构DEVS(DSDEVS)应用于单元空间建模并进行了全面的性能测量。 DSDEVS通过使仿真仅集中于那些活动模型来提高仿真性能,因此比加载整个蜂窝空间时更有效。为了减少由于大量消息在单元之间传递而导致的仿真周期数,我们开发了一种预先计划的建模方法,该方法利用模型行为来提高仿真性能。在网络层,我们开发了一种改进的时间扭曲算法,该算法支持基于DEVS的蜂窝空间模型的并行仿真。所开发的方法已应用于基于DEVS-FIRE模拟环境的大规模野火蔓延模拟,并取得了显着的性能结果。索引词:DEVS,高性能,蜂窝空间,动态结构,建模和模拟,时间扭曲乐观,并行和分布式计算。

著录项

  • 作者

    Sun, Yi.;

  • 作者单位

    Georgia State University.;

  • 授予单位 Georgia State University.;
  • 学科 Computer Science.
  • 学位 Ph.D.
  • 年度 2009
  • 页码 153 p.
  • 总页数 153
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号