CSonNet: An Agent-Based Modeling Software System for Discrete Time Simulation
CSonNet: An Agent-Based Modeling Software System for Discrete Time Simulation
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DOI：
10.1109/wsc52266.2021.9715287
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发表时间：
2021-12
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影响因子：
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通讯作者：
Joshua D. Priest;Aparna Kishore;Lucas Machi;C. Kuhlman;D. Machi;Sujith Ravi
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作者：
Joshua D. Priest;Aparna Kishore;Lucas Machi;C. Kuhlman;D. Machi;Sujith Ravi
网络上的传染动力学被用来研究许多问题，包括疾病和病毒流行、监禁、肥胖、抗议和叛乱、共用毒品的针头以及飓风和其他自然灾害事件。研究这些问题的模拟器范围从较小规模的串行码到大规模的分布式系统。近年来，基于Python的仿真系统相继问世。在这项工作中，我们描述了一个新的基于Python的基于代理的模拟器CSonNet。它与网络上的流行病等代码的不同之处在于，它基于图动态系统形式化执行离散时间模拟。CSonNet是一种并行代码；它通过一种令人尴尬的并行方法实现并发，即在用户指定数量的分叉进程上运行多个模拟实例。它有一个建模框架，其中代理模型是使用一组预定义的状态转换规则来组合的。我们提供了强伸缩性能结果和案例研究来说明其特点。
Contagion dynamics on networks are used to study many problems, including disease and virus epidemics, incarceration, obesity, protests and rebellions, needle sharing in drug use, and hurricane and other natural disaster events. Simulators to study these problems range from smaller-scale serial codes to large-scale distributed systems. In recent years, Python-based simulation systems have been built. In this work, we describe a new Python-based agent-based simulator called CSonNet. It differs from codes such as Epidemics on Networks in that it performs discrete time simulations based on the graph dynamical systems formalism. CSonNet is a parallel code; it implements concurrency through an embarrassingly parallel approach of running multiple simulation instances on a user-specified number of forked processes. It has a modeling framework whereby agent models are composed using a set of pre-defined state transition rules. We provide strong-scaling performance results and case studies to illustrate its features.