Compositional safe approximation of response time probability density function of complex workflows

IF 0.7 4区 计算机科学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ACM Transactions on Modeling and Computer Simulation Pub Date : 2023-04-05 DOI:10.1145/3591205
L. Carnevali, Marco Paolieri, R. Reali, E. Vicario
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引用次数: 1

Abstract

We evaluate a stochastic upper bound on the response time Probability Density Function (PDF) of complex workflows through an efficient and accurate compositional approach. Workflows consist of activities having generally distributed stochastic durations with bounded supports, composed through sequence, choice/merge, and balanced/unbalanced split/join operators, possibly breaking the structure of well-formed nesting. Workflows are specified using a formalism defined in terms of Stochastic Time Petri Nets (STPNs), that permits decomposition into a hierarchy of subworkflows with positively correlated response times, guaranteeing that a stochastically larger end-to-end response time PDF is obtained when intermediate results are approximated by stochastically larger PDFs and when dependencies are simplified by replicating activities appearing in multiple subworkflows. In particular, an accurate stochastically larger PDF is obtained by combining shifted truncated Exponential terms with positive or negative rates. Experiments are performed on sets of manually and randomly generated models with increasing complexity, illustrating under which conditions different decomposition heuristics work well in terms of accuracy and complexity, and showing that the proposed approach outperforms simulation having the same execution time.
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复杂工作流响应时间概率密度函数的组合安全逼近
通过一种高效、准确的组合方法,我们评估了复杂工作流响应时间概率密度函数(PDF)的随机上界。工作流由具有一般分布的随机持续时间和有限支持的活动组成,通过序列、选择/合并和平衡/不平衡分割/连接操作符组成,可能会破坏格式良好的嵌套结构。工作流使用随机时间Petri网(stpn)定义的形式来指定,该形式允许分解为具有正相关响应时间的子工作流层次结构,保证当中间结果由随机较大的PDF近似时获得随机较大的端到端响应时间PDF,并且通过复制多个子工作流中出现的活动来简化依赖关系时获得随机较大的端到端响应时间PDF。特别地,通过将移位的截断指数项与正负速率相结合,获得了精确的随机较大的PDF。在人工和随机生成的复杂模型上进行了实验,说明了不同的分解启发式方法在精度和复杂性方面的工作条件,并表明在相同的执行时间下,所提出的方法优于仿真。
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来源期刊
ACM Transactions on Modeling and Computer Simulation
ACM Transactions on Modeling and Computer Simulation 工程技术-计算机:跨学科应用
CiteScore
2.50
自引率
22.20%
发文量
29
审稿时长
>12 weeks
期刊介绍: The ACM Transactions on Modeling and Computer Simulation (TOMACS) provides a single archival source for the publication of high-quality research and developmental results referring to all phases of the modeling and simulation life cycle. The subjects of emphasis are discrete event simulation, combined discrete and continuous simulation, as well as Monte Carlo methods. The use of simulation techniques is pervasive, extending to virtually all the sciences. TOMACS serves to enhance the understanding, improve the practice, and increase the utilization of computer simulation. Submissions should contribute to the realization of these objectives, and papers treating applications should stress their contributions vis-á-vis these objectives.
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