高等数学在教学绩效建模中的作用

Q4 Computer Science
Ziv Scully
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引用次数: 0

摘要

在没有深厚的数学背景的情况下,我们应该如何教授性能建模?一种方法是专注于严格研究相对简单的随机模型,不需要太多的数学背景。但这可能会让学生在实践中对系统进行推理时准备不足。它们有多个服务器,突然到达,重尾,以及其他需要更复杂的随机模型的特征。对这些现象的推理需要性能建模理论中的高级工具,但严格学习这些工具需要比许多计算机科学和工程专业学生更多的数学背景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Role of Advanced Math in Teaching Performance Modeling
How should we teach performance modeling without assuming a deep mathematical background? One approach is to focus on rigorously studying relatively simple stochastic models that do not require too much math background. But this may leave students underprepared to reason about systems in practice. They have multiple servers, bursty arrivals, heavy tails, and other features that demand more complex stochastic models. Reasoning about these phenomena calls for advanced tools from performance modeling theory, but rigorously learning such tools requires more math background than many computer science and engineering students have.
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来源期刊
Performance Evaluation Review
Performance Evaluation Review Computer Science-Computer Networks and Communications
CiteScore
1.00
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0.00%
发文量
193
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