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CollabOffloading: A Computational Offloading Methodology Using External Clouds for Limited Private On-Site Edge Servers

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Book cover Methods and Applications for Modeling and Simulation of Complex Systems (AsiaSim 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1636))

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Abstract

In this paper, we proposed a methodology using Kubernetes clustered on-site edge servers with external clouds to provide computational offloading functionality for resource-limited private edge servers. This methodology enables additional functionalities without changing hardware infrastructures for industrial areas such as manufacturing systems. We devised a compute-intensive task scheduling algorithm using real-time CPU usage information of Kubernetes cluster to determine computation offloading decision. The purpose of the experiment is to compare overall performance between on-site edge only cluster and external cloud offloading cluster. The experiment scenario contains complex simulation problem which selects optimal tollgate for congested traffic situation. The result of experiment shows the proposed CollabOffloading methodology reduces entire execution time of simulations.

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References

  1. Nam, S.: The impact of 5G multi‐access edge computing cooperation announcement on the telecom operators’ firm value. 44(4), 588–598 ETRI J. (2022)

    Google Scholar 

  2. Yu, B., Hu, W., Xu, L., Tang, J., Liu, S., Zhu, Y.: Building the computing system for autonomous micromobility vehicles: design constraints and architectural optimizations. In: 53rd IEEE/ACM International Symposium on Microarchitecture, pp. 1067–1081. Global Online Event (2020)

    Google Scholar 

  3. Lee, J., Kang, S., Jeon, J., Chun, I.: Multiaccess edge computing-based simulation as a service for 5G mobile applications: a case study of tollgate selection for autonomous vehicles. Wirel. Commun. Mob. Comput (2020)

    Google Scholar 

  4. Rosendo, D., Silve, P., Simonin, M., Costan, A., Antoniu, G.: E2Clab: exploring the computing continuum through repeatable, replicable and reproducible edge-to-cloud experiments. In: 2020 IEEE International Conference on Cluster Computing, Kobe, Japan, pp. 176–186 (2020)

    Google Scholar 

  5. Balouek-Thomert, D., Renart, E.G., Zamani, A.R., Simonet, A., Parashar, M.: Towards a computing continuum: enabling edge-to-cloud integration for data-driven workflows. Int. J. High Perform. Comput. Appl. 33(6), 1159–1174 (2019)

    Article  Google Scholar 

  6. Ella, P., Arun, S., Tero, P.: Towards real-time learning for edge-cloud continuum with vehicular computing. In: IEEE 7th World Forum on Internet of Things, New Orleans, LA, United States, pp. 921–926 (2021)

    Google Scholar 

  7. Kubernetes. https://kubernetes.io/. Accessed 08 July 2022

  8. Kubernetes Scheduling Framework. https://kubernetes.io/docs/concepts/scheduling-eviction/scheduling-framework/. Accessed 08 July 2022

  9. Kubernetes Scheduler Plugins. https://kubernetes.io/docs/reference/scheduling/config. Accessed 08 July 2022

  10. Amazon Web Services. https://aws.amazon.com/. Accessed 08 July 2022

  11. Google Cloud Platform. https://cloud.google.com/. Accessed 08 July 2022

  12. Microsoft Azure. https://azure.microsoft.com. Accessed 08 July 2022

  13. Naver Cloud. https://www.navercloudcorp.com/. Accessed 08 July 2022

  14. Calico. https://projectcalico.docs.tigera.io/about/about-calico. Accessed 08 July 2022

  15. Mahadevan, S.: Monte Carlo simulation. Mechanical Engineering-New York and Basel-Marcel Dekker, pp. 123–146 (1997)

    Google Scholar 

  16. kube-ops-view. https://github.com/hjacobs/kube-ops-view. Accessed 08 July 2022

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Acknowledgement

This work was supported by Institute of Information & communications Technology Planning & Evaluation(IITP) grant funded by the Korea government(MSIT) (No. 2020-0-00844, Development of Lightweight System Software Technology for Resource Management and Control of Edge Server Systems).

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Authors and Affiliations

  1. Electronics and Telecommunications Research Institute (ETRI), Daejeon, Republic of Korea

    Junhee Lee, Jaeho Jeon & Sungjoo Kang

  2. Korea Advanced Institute of Science and Technology (KAIST) , Daejeon, Republic of Korea

    Junhee Lee

Authors
  1. Junhee Lee
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  2. Jaeho Jeon
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  3. Sungjoo Kang
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Corresponding author

Correspondence to Sungjoo Kang .

Editor information

Editors and Affiliations

  1. Ajou University, Suwon, Korea (Republic of)

    Byeong-Yun Chang

  2. Hanbat National University, Daejeon, Korea (Republic of)

    Changbeom Choi

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Lee, J., Jeon, J., Kang, S. (2022). CollabOffloading: A Computational Offloading Methodology Using External Clouds for Limited Private On-Site Edge Servers. In: Chang, BY., Choi, C. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2021. Communications in Computer and Information Science, vol 1636. Springer, Singapore. https://doi.org/10.1007/978-981-19-6857-0_5

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  • DOI: https://doi.org/10.1007/978-981-19-6857-0_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-6856-3

  • Online ISBN: 978-981-19-6857-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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