More Web Proxy on the site http://driver.im/

research-article

Advanced Models for the Simulation of AGV Communication in Industrial Environments: Model proposal and Demonstration

Authors:

Christian Sauer,

Maja SliskovicAuthors Info & Claims

DIVANet '20: Proceedings of the 10th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications

Pages 25 - 32

https://doi.org/10.1145/3416014.3424604

Published: 16 November 2020 Publication History

Abstract

Wireless communication continuously gains importance in the industrial environment. Mobile communication, for example between Automated Guided Vehicles (AGVs), is a particularly challenging use case. The AGVs move in the industrial environment and require a connection to a central controller by means of wireless communication technologies. Most AGVs can not move without this connection. On the other hand the AGVs mobility effects the available communication channels. Therefore mobility and communication are directly linked in this use case. Common mobility and signal propagation models are not suitable to model these links and the emerging AGV behavior.

In this work a new model structure for the simulation and evaluation of mobile wireless networks in the industrial context is proposed. A newly proposed mobility model is the core of this new model structure, which enables the evaluation of the communication networks effects on the mobile systems performance and behavior.

References

[1]

Eike Lyczkowski, Andreas Wanjek, and Christian Sauer. Wireless communication in industrial applications. In IEEE 24th International Conference on Emerging Technologies and Factory Automation (ETFA), 2019.

Digital Library

[2]

A Lagar Cavilla, Gerard Baron, Thomas E Hart, Lionel Litty, and Eyal De Lara. Simplified simulation models for indoor manet evaluation are not robust. In Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004. 2004 First Annual IEEE Communications Society Conference on, pages 610--620. IEEE, 2004.

[3]

Josh Broch, David A Maltz, David B Johnson, Yih-Chun Hu, and Jorjeta Jetcheva. A performance comparison of multi-hop wireless ad hoc network routing protocols. In Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networking, pages 85--97. ACM, 1998.

Digital Library

[4]

Gustaf Lindstedt. Simulation & analysis of peer-to-peer network quality for measurement scheduling: Online algorithms, application for network qos monitoring. Degree project, KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCE, Stockholm, Sweden, January 2019.

[5]

Christian Bettstetter, Hannes Hartenstein, and Xavier Pérez-Costa. Stochastic properties of the random waypoint mobility model. Wireless Networks, 10(5):555--567, 2004.

Digital Library

[6]

Thomas R Henderson, Mathieu Lacage, George F Riley, Craig Dowell, and Joseph Kopena. Network simulations with the ns-3 simulator. SIGCOMM demonstration, 14(14):527, 2008.

[7]

Lokesh Bajaj, Mineo Takai, Rajat Ahuja, Ken Tang, Rajive Bagrodia, and Mario Gerla. Glomosim: A scalable network simulation environment. UCLA computer science department technical report, 990027(1999):213, 1999.

[8]

Nathan Koenig and Andrew Howard. Design and use paradigms for gazebo, an open-source multi-robot simulator. In Intelligent Robots and Systems, 2004.(IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on, volume 3, pages 2149--2154. IEEE, 2004.

[9]

Brian Gerkey, Richard T Vaughan, and Andrew Howard. The player/stage project: Tools for multi-robot and distributed sensor systems. In Proceedings of the 11th international conference on advanced robotics, volume 1, pages 317--323, 2003.

[10]

Carlo Pinciroli, Vito Trianni, Rehan O'Grady, Giovanni Pini, Arne Brutschy, Manuele Brambilla, Nithin Mathews, Eliseo Ferrante, Gianni Di Caro, Frederick Ducatelle, et al. Argos: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm intelligence, 6(4):271--295, 2012.

[11]

Michal Kudelski, Luca M Gambardella, and Gianni A Di Caro. Robonetsim: An integrated framework for multi-robot and network simulation. Robotics and Autonomous Systems, 61(5):483--496, 2013.

Digital Library

[12]

Miguel Calvo-Fullana, Daniel Mox, Alexander Pyattaev, Jonathan Fink, Vijay Kumar, and Alejandro Ribeiro. Ros-netsim: A framework for the integration of robotic and network simulators. Preprint, 2020.

[13]

Mate Boban, Joao Barros, and Ozan K Tonguz. Geometry-based vehicle-to-vehicle channel modeling for large-scale simulation. IEEE Transactions on Vehicular Technology, 63(9):4146--4164, 2014.

[14]

Vu Khanh Quy, Nguyen Tien Ban, Vi Hoai Nam, Dao Minh Tuan, and Nguyen Dinh Han. Survey of recent routing metrics and protocols for mobile ad-hoc networks. Journal of Communications, 14(2), 2019.

[15]

Cristina Aurrecoechea, Andrew T Campbell, and Linda Hauw. A survey of qos architectures. Multimedia systems, 6(3):138--151, 1998.

Digital Library

[16]

Prasant Mohapatra, Jian Li, and Chao Gui. Qos in mobile ad hoc networks. IEEE Wireless Communications, 10(3):44--53, 2003.

Digital Library

[17]

Elnaz Alizadeh Jarchlo, Jetmir Haxhibeqiri, Ingrid Moerman, and Jeroen Hoebeke. To mesh or not to mesh: flexible wireless indoor communication among mobile robots in industrial environments. In International Conference on Ad Hoc Networks and Wireless (AdHoc-Now2016), pages 1--14. Ghent University -- iMinds, Department of Information Technology (INTEC), Ghent University, 2016.

[18]

Christian Sauer, Marco Schmidt, and Maja Sliskovic. Delay tolerant networks in industrial applications. In IEEE 24th International Conference on Emerging Technologies and Factory Automation (ETFA), 2019.

Digital Library

[19]

Jing Tian, Jorg Hahner, Christian Becker, Illya Stepanov, and Kurt Rothermel. Graph-based mobility model for mobile ad hoc network simulation. In Proceedings 35th Annual Simulation Symposium. SS 2002, pages 337--344. IEEE, 2002.

Digital Library

[20]

Tapan K Sarkar, Zhong Ji, Kyungjung Kim, Abdellatif Medouri, and Magdalena Salazar-Palma. A survey of various propagation models for mobile communication. IEEE Antennas and propagation Magazine, 45(3):51--82, 2003.

[21]

Dylan A Shell and Maja J Matarić. High-fidelity radio communications modeling for multi-robot simulation. In Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on, pages 3447--3452. IEEE, 2009.

Digital Library

[22]

Charles Perkins, Elizabeth Belding-Royer, and Samir Das. Ad hoc on-demand distance vector (aodv) routing. Technical report, Network Working Group, 2003.

Digital Library

Cited By

Lien STseng CHung WTsai CLiu TDeng DLin YLin SChang CChang S(2024)Open Radio Access Network RIC Empowered Reconfigurable Intelligent Surface: A Physical-Layer Security PerspectiveIEEE Transactions on Industrial Cyber-Physical Systems10.1109/TICPS.2024.34843722(615-625)Online publication date: 2024
https://doi.org/10.1109/TICPS.2024.3484372
Sauer CLyczkowski ESchmidt MNüchter AHoßfeld T(2022)Testing AGV mobility control method for MANET coverage optimization using procedural simulationComputer Communications10.1016/j.comcom.2022.07.033194(189-201)Online publication date: Oct-2022
https://doi.org/10.1016/j.comcom.2022.07.033
Sauer CLyczkowski ESchmidt MNüchter AHoßfeld TIgartua MGiannelli CZheng J(2021)Testing AGV Mobility Control Method for MANET Coverage Optimization using Procedural GenerationProceedings of the 24th International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems10.1145/3479239.3485724(13-22)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.1145/3479239.3485724

Index Terms

Advanced Models for the Simulation of AGV Communication in Industrial Environments: Model proposal and Demonstration
1. Applied computing
  1. Operations research
    1. Industry and manufacturing
      1. Command and control
2. Networks
  1. Network performance evaluation
    1. Network simulations

Recommendations

An enhanced fast handover with seamless mobility support for next-generation wireless networks

To allow mobile node be always connected regardless of its location on the Internet, mobile IPv6 (MIPv6) is designed for next-generation wireless networks. However, this protocol has some inherent drawbacks: long handoff delay and high packet loss; ...
DIP-MIP: Distributed individual paging extension for mobile IP in IP-based cellular networks

The mobility-enabling protocol Mobile IP supports location registration but not paging. However, current cellular networks use registration as well as paging procedures to minimize signaling cost. Accordingly, an extension to Mobile IP using distributed ...
Stochastic properties and application of city section mobility model
GLOBECOM'09: Proceedings of the 28th IEEE conference on Global telecommunications

Node mobility has a direct impact on the performance evaluation of various network mobility protocols. Unfortunately, most of the analysis on mobility protocols used Random Waypoint mobility model which does not represent real-world movement patterns of ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

DIVANet '20: Proceedings of the 10th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications

November 2020

76 pages

ISBN:9781450381215

DOI:10.1145/3416014

General Chair:
Mirela Notare
Technology University on Fly Transportation, Brazil
,
Program Chair:
Peng Sun
Duke Kunshan University, China

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGSIM: ACM Special Interest Group on Simulation and Modeling

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 November 2020

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

MSWiM '20

Sponsor:

SIGSIM

MSWiM '20: 23rd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

November 16 - 20, 2020

Alicante, Spain

Acceptance Rates

Overall Acceptance Rate 70 of 308 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
107
Total Downloads

Downloads (Last 12 months)20
Downloads (Last 6 weeks)1

Reflects downloads up to 05 Jan 2025

Other Metrics

View Author Metrics

Citations

Cited By

Lien STseng CHung WTsai CLiu TDeng DLin YLin SChang CChang S(2024)Open Radio Access Network RIC Empowered Reconfigurable Intelligent Surface: A Physical-Layer Security PerspectiveIEEE Transactions on Industrial Cyber-Physical Systems10.1109/TICPS.2024.34843722(615-625)Online publication date: 2024
https://doi.org/10.1109/TICPS.2024.3484372
Sauer CLyczkowski ESchmidt MNüchter AHoßfeld T(2022)Testing AGV mobility control method for MANET coverage optimization using procedural simulationComputer Communications10.1016/j.comcom.2022.07.033194(189-201)Online publication date: Oct-2022
https://doi.org/10.1016/j.comcom.2022.07.033
Sauer CLyczkowski ESchmidt MNüchter AHoßfeld TIgartua MGiannelli CZheng J(2021)Testing AGV Mobility Control Method for MANET Coverage Optimization using Procedural GenerationProceedings of the 24th International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems10.1145/3479239.3485724(13-22)Online publication date: 22-Nov-2021
https://dl.acm.org/doi/10.1145/3479239.3485724

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents