分布式数据采集系统的事件与过程联合仿真模型

H. Bahr
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引用次数: 1

摘要

事件和过程驱动仿真技术的发展,以评估负载和吞吐量在一个多处理器为基础的分布式数据采集系统。利用这两种仿真技术的各个方面来促进快速模型开发,同时保留灵活的配置参数选择。正常和优先级玩家的扩展能力和延迟时间的统计数据表明,总线流量本身不是一个限制参数,除非进程大小超过本地内存容量。然而,除非适当平衡,否则通道加载可能导致严重的延迟。
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Combined event & process simulation model of a distributed data collection system
Event and process driven simulation techniques are developed to assess loading and throughput in a multiprocessor-based distributed data collection system. Aspects of both simulation techniques are utilized to facilitate rapid model development while retaining flexible selection of configuration parameters. Statistics obtained for expansion capability and latency times for normal and priority players indicate bus traffic itself is not a limiting parameter unless process size exceeds local memory capacity. However, channel loading can cause significant delays unless properly balanced.
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