research-article

Connectivity Management in an Integrated Heterogeneous Social Networks Framework in Vehicular Environments

Authors:

Huong Nguyen Minh,

Anna Maria Vegni,

Valeria Loscrí,

Abderrahim BenslimaneAuthors Info & Claims

GoodIT '21: Proceedings of the Conference on Information Technology for Social Good

Pages 25 - 30

https://doi.org/10.1145/3462203.3475899

Published: 09 September 2021 Publication History

Abstract

In the last decade, Online Social Networks (OSNs) have emerged as one of the most disruptive communication platforms with high socio-economic value, used every day by billions of users to connect with friends, colleagues, and any other user with social ties and common interests. Social features are pervasively penetrating in our daily life not only by means of OSNs, but also in other contexts, such as that of vehicular ad-hoc networks. Vehicular Social Networks (VSNs) are enhanced with social features that impact not only on societal services, but especially on connectivity and communication performance. As a result, the coexistence of both OSNs and VSNs can represent a benefit for both two domains, allowing the creation of a unique network framework for connectivity maintenance.

This paper presents a connectivity management technique in a heterogeneous network framework, namely SOLVER, comprised of both OSN and VSN communities for data exchange among nodes belonging to different networks. Connectivity switching is allowed in case of expected connectivity loss, as well as degradation of network performance. Results assess the effectiveness of SOLVER framework as compared to traditional Client-Server and Peer-to-Peer architectural modes.

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Cited By

Nguyen-Minh HTran Hoang TPham Thanh G(2023)Machine Learning-Based Jamming Detection for Safety Applications in Vehicular NetworksSecurity and Communication Networks10.1155/2023/80806692023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/8080669
Giang ATran HLe HDoan NNguyen M(2022)Jamming Attack in Vehicular NetworksWireless Communications & Mobile Computing10.1155/2022/38847612022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/3884761

Index Terms

Connectivity Management in an Integrated Heterogeneous Social Networks Framework in Vehicular Environments
1. Networks
  1. Network performance evaluation
  2. Network types
    1. Ad hoc networks
    2. Packet-switching networks

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cover image ACM Conferences

GoodIT '21: Proceedings of the Conference on Information Technology for Social Good

September 2021

345 pages

ISBN:9781450384780

DOI:10.1145/3462203

Copyright © 2021 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]

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Published: 09 September 2021

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GoodIT '21

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GoodIT '21: Conference on Information Technology for Social Good

September 9 - 11, 2021

Roma, Italy

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Cited By

Nguyen-Minh HTran Hoang TPham Thanh G(2023)Machine Learning-Based Jamming Detection for Safety Applications in Vehicular NetworksSecurity and Communication Networks10.1155/2023/80806692023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/8080669
Giang ATran HLe HDoan NNguyen M(2022)Jamming Attack in Vehicular NetworksWireless Communications & Mobile Computing10.1155/2022/38847612022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/3884761

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