An Orchestrator Framework for IoT-based Disaster Prevention Simulation

被引：0

作者：

Hiroi, Kei ^{[1
]}

Kohiga, Akihito ^{[2
]}

Fukaya, Sho ^{[3
]}

Shinoda, Yoichi ^{[2
]}

机构：

[1] Kyoto Univ, Disaster Prevent Res Inst, Kyoto, Japan

[2] Japan Adv Inst Sci & Technol, Nomi, Japan

[3] Suwa Univ Sci, Chino, Japan

来源：

2023 IEEE SENSORS | 2023年

关键词：

IoT-based Simulation; Crisis Management IT system component; Digital Twin; EVACUATION; MODEL;

D O I：

10.1109/SENSORS56945.2023.10325055

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Human casualties from flooding are caused by various factors, such as damage caused by flood water, delays in evacuation due to road flooding or communication network failures, or accidents during evacuation. However, conventional simulations (e.g., river flooding, road flooding, and communication failures) are developed as proprietary systems, and it is difficult to use them to estimate and predict phenomena or casualties related to flood damage. This paper proposes an orchestrator framework for IoT-based disaster prevention simulation, which simulates urban flooding, numbers of affected people, and network failures in an integrated manner. We develop an orchestration scheme that coordinates several independent simulators into one simulation to observe mutually related phenomena (e.g., evacuation behavior in a flood simulation). Our orchestration scheme deploys the simulators, data exchange system, and virtual clock system on a Kubernetes cluster and controls the synchronization and execution order of these simulators. We describe our orchestration scheme architecture, automatic determination of the execution order, and detection of misconfigurations for the continuous operation of multiple simulators.

引用

页数：4

共 25 条

[1] [Anonymous], INTERGOVERNMENTAL PA
[2] Simulation of wildfire evacuation with dynamic factors and model composition
Beloglazov, Anton
Almashor, Mahathir
Abebe, Ermyas
Richter, A. Jan
Steer, Kent Charles Barton
[J]. SIMULATION MODELLING PRACTICE AND THEORY, 2016, 60 : 144 - 159
[3] Boschert S., 2016, Mechatronic Futures, P59, DOI [DOI 10.1007/978-3-319-32156-1_5, 10.1007/978-3-319-32156-15, DOI 10.1007/978-3-319-32156-15]
[4] Modeling pedestrian flow accounting for collision avoidance during evacuation
Chen, Liang
Tang, Tie-Qiao
Huang, Hai-Jun
Wu, Jian-Jun
Song, Ziqi
[J]. SIMULATION MODELLING PRACTICE AND THEORY, 2018, 82 : 1 - 11
[5] High level architecture for simulation: An update
Dahmann, JS
Morse, KL
[J]. 2ND INTERNATIONAL WORKSHOP ON DISTRIBUTED INTERACTIVE SIMULATION AND REAL-TIME APPLICATIONS, PROCEEDINGS, 1998, : 32 - 40
[6] Estrela VaniaV., 2017, BRAZ TECHN S, P319
[7] An HLA-based multiagent system for optimized resource allocation after strong earthquakes
Fiedrich, Frank
[J]. Proceedings of the 2006 Winter Simulation Conference, Vols 1-5, 2006, : 486 - 492
[8] Hwang S, 2016, WINT SIMUL C PROC, P3365, DOI 10.1109/WSC.2016.7822367
[9] Virtual Singapore integration with energy simulation and canopy modelling for climate assessment
Ignatius, M.
Wong, N. H.
Martin, M.
Chen, S.
[J]. SUSTAINABLE BUILT ENVIRONMENT CONFERENCE 2019 TOKYO (SBE19TOKYO) - BUILT ENVIRONMENT IN AN ERA OF CLIMATE CHANGE: HOW CAN CITIES AND BUILDINGS ADAPT?, 2019, 294
[10] A framework for modeling and simulation for emergency response
Jain, S
McLean, C
[J]. PROCEEDINGS OF THE 2003 WINTER SIMULATION CONFERENCE, VOLS 1 AND 2, 2003, : 1068 - 1076

← 1 2 3 →