Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs

Jeong Min Jeon; Choong Seon Hong

doi:10.1109/icoin50884.2021.9333988

Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs

Jeong Min Jeon, Choong Seon Hong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

With the recent development of the Internet of Things (IoT), applications are becoming smarter and connected devices are being used in all aspects. As the amount of collected data increases, machine learning (ML) technology has been applied and is being used as a useful tool for extracting vast amounts of information. If the data set is wide and distributed, old machine learning algorithms cannot be used because the whole training data should be centralized in one location. Therefore, distributed learning, federated learning, and circular learning are being used. In this paper, we propose a new Trust-based Edge network architecture that is suitable for distributed learning and hierarchical machine learning in a Vehicular ad-hoc network(VANETs) it is inspired by Dempster-Shafer theory with Scalable Chord Peer to Peer Network. In order to cut down on computation, communication costs, and time.

Original language	English
Title of host publication	35th International Conference on Information Networking, ICOIN 2021
Publisher	IEEE Computer Society
Pages	627-629
Number of pages	3
ISBN (Electronic)	9781728191003
DOIs	https://doi.org/10.1109/icoin50884.2021.9333988
Publication status	Published - 13 Jan 2021
Event	35th International Conference on Information Networking, ICOIN 2021 - Jeju Island, Korea, Republic of Duration: 13 Jan 2021 → 16 Jan 2021

Publication series

Name	International Conference on Information Networking
Volume	2021-January
ISSN (Print)	1976-7684

Conference

Conference	35th International Conference on Information Networking, ICOIN 2021
Country/Territory	Korea, Republic of
City	Jeju Island
Period	13/01/21 → 16/01/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

Communication cost
Dempster-Shafer theory
Network Architecture
chord P2P Network

Access to Document

10.1109/icoin50884.2021.9333988

Cite this

Jeon, J. M., & Hong, C. S. (2021). Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs. In 35th International Conference on Information Networking, ICOIN 2021 (pp. 627-629). Article 9333988 (International Conference on Information Networking; Vol. 2021-January). IEEE Computer Society. https://doi.org/10.1109/icoin50884.2021.9333988

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title = "Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs",

abstract = "With the recent development of the Internet of Things (IoT), applications are becoming smarter and connected devices are being used in all aspects. As the amount of collected data increases, machine learning (ML) technology has been applied and is being used as a useful tool for extracting vast amounts of information. If the data set is wide and distributed, old machine learning algorithms cannot be used because the whole training data should be centralized in one location. Therefore, distributed learning, federated learning, and circular learning are being used. In this paper, we propose a new Trust-based Edge network architecture that is suitable for distributed learning and hierarchical machine learning in a Vehicular ad-hoc network(VANETs) it is inspired by Dempster-Shafer theory with Scalable Chord Peer to Peer Network. In order to cut down on computation, communication costs, and time.",

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doi = "10.1109/icoin50884.2021.9333988",

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Jeon, JM & Hong, CS 2021, Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs. in 35th International Conference on Information Networking, ICOIN 2021., 9333988, International Conference on Information Networking, vol. 2021-January, IEEE Computer Society, pp. 627-629, 35th International Conference on Information Networking, ICOIN 2021, Jeju Island, Korea, Republic of, 13/01/21. https://doi.org/10.1109/icoin50884.2021.9333988

Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs. / Jeon, Jeong Min; Hong, Choong Seon.
35th International Conference on Information Networking, ICOIN 2021. IEEE Computer Society, 2021. p. 627-629 9333988 (International Conference on Information Networking; Vol. 2021-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Scalable Private P2P network for distributed and Hierarchical Machine Learning in VANETs

Abstract

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Keywords

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