Time granularity impact on propagation of disruptions in a system-of-systems simulation of infrastructure and business networks

التفاصيل البيبلوغرافية
العنوان: Time granularity impact on propagation of disruptions in a system-of-systems simulation of infrastructure and business networks
المؤلفون: Dubaniowski, Mateusz Iwo, Heinimann, Hans Rudolf
سنة النشر: 2021
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Social and Information Networks, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Multiagent Systems, Electrical Engineering and Systems Science - Systems and Control
الوصف: System-of-systems (SoS) approach is often used for simulating disruptions to business and infrastructure system networks allowing for integration of several models into one simulation. However, the integration is frequently challenging as each system is designed individually with different characteristics, such as time granularity. Understanding the impact of time granularity on propagation of disruptions between businesses and infrastructure systems and finding the appropriate granularity for the SoS simulation remain as major challenges. To tackle these, we explore how time granularity, recovery time, and disruption size affect the propagation of disruptions between constituent systems of an SoS simulation. To address this issue, we developed a High Level Architecture (HLA) simulation of 3 networks and performed a series of simulation experiments. Our results revealed that time granularity and especially recovery time have huge impact on propagation of disruptions. Consequently, we developed a model for selecting an appropriate time granularity for an SoS simulation based on expected recovery time. Our simulation experiments show that time granularity should be less than 1.13 of expected recovery time. We identified some areas for future research centered around extending the experimental factors space.
Comment: 26 pages, 11 figures, 2 tables, Submitted to International Journal of Environmental Research and Public Health: Special Issue on Cascading Disaster Modelling and Prevention
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2103.03247
رقم الأكسشن: edsarx.2103.03247
قاعدة البيانات: arXiv