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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A traffic data clustering framework based on fog computing for VANETs

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Author(s):
Peixoto, M. L. M. [1, 2] ; Maia, A. H. O. [2] ; Mota, E. [2] ; Rangel, E. [2] ; Costa, D. G. [3] ; Turgut, D. [4] ; Villas, L. A. [1]
Total Authors: 7
Affiliation:
[1] Univ Campinas UNICAMP, Inst Comp, Campinas, SP - Brazil
[2] Fed Univ Bahia UFBA, Comp Sci Dept, Salvador, BA - Brazil
[3] State Univ Feira de Santana, Dept Technol, Feira De Santana, BA - Brazil
[4] Univ Cent Florida, Dept Comp Sci, Orlando, FL 32816 - USA
Total Affiliations: 4
Document type: Journal article
Source: VEHICULAR COMMUNICATIONS; v. 31, OCT 2021.
Web of Science Citations: 0
Abstract

Vehicular Ad-hoc Networks (VANETs) are based on vehicle to infrastructure communications in which the vehicles periodically broadcast information to update a Road Side Unit (RSU). The traffic data is forwarded from all RSUs to a cloud or a central server for global analysis and detection of congestion levels on the roads. However, communication costs may considerably increase when a large amount of data is transmitted to such cloud-like service providers. In this paper, we propose a data clustering framework to perform traffic information reduction at the edge of vehicular networks by exploiting fog computing. The proposed data clustering framework defines two methods for the reduction of the traffic data stream: (i) Baseline method, which is an ordinary traffic congestion detection approach, and (ii) two adapted clustering methods for a data stream; namely, the Ordering Points to Identify the Clustering Structure (OPTICS) and the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). The results have shown that the proposed traffic data framework using clustering methods is accurate even when the vehicular traffic condition is highly congested, potentially reducing the communication costs and bringing significant results for the development of VANETs. (C) 2021 Elsevier Inc. All rights reserved. (AU)

FAPESP's process: 18/23126-3 - Data Orchestration for Urban Computing through Fog Computing
Grantee:Maycon Leone Maciel Peixoto
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 15/24494-8 - Communications and processing of big data in cloud and fog computing
Grantee:Nelson Luis Saldanha da Fonseca
Support Opportunities: Research Projects - Thematic Grants