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Multiple-Junction-Based Traffic-Aware Routing Protocol Using ACO Algorithm in Urban Vehicular Networks.
Lee, Seung-Won; Heo, Kyung-Soo; Kim, Min-A; Kim, Do-Kyoung; Choi, Hoon.
Afiliação
  • Lee SW; Department of C4I Research, LIG Nex1, Seongnam 13488, Republic of Korea.
  • Heo KS; Department of C4I Research, LIG Nex1, Seongnam 13488, Republic of Korea.
  • Kim MA; Department of C4I Research, LIG Nex1, Seongnam 13488, Republic of Korea.
  • Kim DK; Department of C4I Research, LIG Nex1, Seongnam 13488, Republic of Korea.
  • Choi H; Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, Republic of Korea.
Sensors (Basel) ; 24(9)2024 May 02.
Article em En | MEDLINE | ID: mdl-38733019
ABSTRACT
The burgeoning interest in intelligent transportation systems (ITS) and the widespread adoption of in-vehicle amenities like infotainment have spurred a heightened fascination with vehicular ad-hoc networks (VANETs). Multi-hop routing protocols are pivotal in actualizing these in-vehicle services, such as infotainment, wirelessly. This study presents a novel protocol called multiple junction-based traffic-aware routing (MJTAR) for VANET vehicles operating in urban environments. MJTAR represents an advancement over the improved greedy traffic-aware routing (GyTAR) protocol. MJTAR introduces a distributed mechanism capable of recognizing vehicle traffic and computing curve metric distances based on two-hop junctions. Additionally, it employs a technique to dynamically select the most optimal multiple junctions between source and destination using the ant colony optimization (ACO) algorithm. We implemented the proposed protocol using the network simulator 3 (NS-3) and simulation of urban mobility (SUMO) simulators and conducted performance evaluations by comparing it with GSR and GyTAR. Our evaluation demonstrates that the proposed protocol surpasses GSR and GyTAR by over 20% in terms of packet delivery ratio, with the end-to-end delay reduced to less than 1.3 s on average.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article