Distribution-invariance in agent-based spatial simulations

IF 6.2 2区计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS

Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-08-18 DOI:10.1016/j.future.2025.108054

Mateusz Paciorek, Wojciech Turek

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引用次数: 0

Abstract

Large-scale spatial simulations of social beings often exceed the processing capabilities of a single computer. Efficient parallelization and distribution of such simulations is typically based on model partitioning and parallel processing of model parts on many computing nodes. In simulation models which consider mutually exclusive actions of agents, such an approach raises significant problems related to synchronization of the borders between environment partitions processed by different computing nodes. This paper addresses this problem and presents an abstract method for achieving distribution transparency in discrete spatial agent-based simulations. It proposes definitions of distribution-invariance in such simulations and a distribution-invariant simulation algorithm together with formal frames to express the model compliant with the algorithm. A verification of the method in the context of the proposed definitions is presented as well as an analysis of the scalability and applicability of the method.

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基于智能体的空间模拟中的分布不变性

对社会存在的大规模空间模拟往往超出了一台计算机的处理能力。这种仿真的高效并行化和分布通常基于模型划分和在多个计算节点上对模型部件进行并行处理。在考虑代理互斥行为的仿真模型中，这种方法引起了与由不同计算节点处理的环境分区之间边界同步相关的重大问题。本文解决了这一问题，并提出了一种抽象的方法来实现离散空间智能体模拟中的分布透明性。提出了分布不变性仿真的定义，给出了一种分布不变性仿真算法，并用形式化框架表示了符合该算法的模型。在提出的定义的背景下验证了该方法，并分析了该方法的可扩展性和适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Future Generation Computer Systems-The International Journal of Escience 工程技术-计算机：理论方法

CiteScore

19.90

自引率

2.70%

发文量

376

审稿时长

10.6 months

期刊介绍： Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.