Work

A Centrality Approach to Select Offloading Data Aggregation Points in Vehicular Sensor Networks

Year: 2023

Type: article

Abstract: This work proposes a centrality-based approach to identify data offloading points in a VSN. The solution presents a scheme to select vehicles used as aggregation points to collect and aggregate other vehicles’ data before uploading it to processing stations. We evaluate the proposed solution in a realistic simulation scenario derived from data traffic containing more than 700,000 individual car trips for 24 hours. We compare our approach with both a reservation-based algorithm and the optimal solution. Our results indicate an upload cost reduction of 30.92% using the centrality-based algorithm and improving the aggregation rate by up to 10.45% when considering the centralized scenario.

Source: IEEE Transactions on Intelligent Transportation Systems

DOI: 10.1109/tits.2023.3297886

Authors: Douglas L. L. Moura, Geymerson S. Ramos, Andre L. L. Aquino, Antonio A. F. Loureiro

Institutions: Universidade Federal de Minas Gerais, Institut National des Sciences Appliquées de Lyon, Universidade Federal de Alagoas

Language: English

Topic: Vehicular Ad Hoc Networks (VANETs)

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: green

Funders: Fundação de Amparo à Pesquisa do Estado de Alagoas, Conselho Nacional de Desenvolvimento Científico e Tecnológico