自我优化数字生态系统的模拟

T. Heistracher, Thomas Kurz
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引用次数: 19

摘要

中小型企业(sme)通常缺乏资源来定制软件解决方案,这些解决方案最好地支持他们的核心业务。本文介绍了一种用于自优化中小企业网络的仿真框架——演化环境模拟器(evessimulator)。框架所基于的进化环境是一个基础设施组件,用于分布式和分散的服务创建和基于在生活环境中类似操作的机制的服务改进。本文主要对中小企业网络的这些机制进行了模拟。在广泛使用的仿真框架Repast的基础上,研究了使用自优化软件服务并在企业之间分发相关信息的企业的合作行为。该模拟器能够从实际业务中导入实际数据,从而实现概念研究和假设检验。它被应用在三种利用场景的背景下,研究可持续性的临界质量,一般的集群和基于使用的集群。EvESimulator的第一个结果揭示了一个不断增长的业务网络的动态创建,从长远来看,它明显优于集中式拓扑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation of a Self-Optimising Digital Ecosystem
Small and medium enterprises (SMEs) most often lack resources for custom-made software solutions that support best their core businesses. In this paper a simulation framework for self-optimising SME networks, namely Evolutionary Environment Simulator (EvESimulator), is introduced. The Evolutionary Environment, which the framework bases on, is an infrastructural component for distributed and decentralised service creation and service improvement based on mechanisms that are operating similarly in the living environment. This paper concentrates on the simulation of these mechanisms for SME networks. Built upon the widely-used simulation framework Repast, the cooperation behaviour of companies is investigated that use self-optimizing software services and distribute related information amongst them. The simulator is capable of importing real-world data from real businesses thereby enabling conceptual studies and hypothesis testing. It is applied in the context of three utilisation scenarios that investigate critical mass for sustainability, clustering in general, and usage-based clustering. The first results of the EvESimulator reveal a dynamic creation of a growing network of businesses that is clearly outperforming centralized topologies in the long run.
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