Back to results

York University

Two Tier Hybrid Routing Schemes for Vehicular Ad Hoc Networks Based on Reinforcement Learning

Abstract

dc:description.abstract

This research addresses the issue of routing messages from vehicles to specific geographical locations in VANETs. To overcome this challenge we propose a hybrid system consisting of traffic-aware located RSUs and a reinforcement learning routing strategy. Our proposed method includes two main tiers. We first divided the geographical area into equal-sized grids; then using the traffic flow patterns of the area, the protocol will suggest the optimal locations for RSUs with the objective of minimizing the number of RSUs in the system to cut down the cost while improving the delivery ratio at the lowest possible delay.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Boroujeni, Narges Haghighati
Advisor dc:contributor.advisor
  • Datta, Suprakash

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
Language dc:language
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10315/38668
OAI identifier oai:identifier
oai:yorkspace.library.yorku.ca:10315/38668

Chain of custody

source
Harvested from
York University
Base URL
yorkspace.library.yorku.ca/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Boroujeni, Narges Haghighati. Two Tier Hybrid Routing Schemes for Vehicular Ad Hoc Networks Based on Reinforcement Learning. 2021. http://hdl.handle.net/10315/38668