relation: https://khub.utp.edu.my/scholars/15358/
title: The best path selection using ant colony optimization and message trust in IoV
creator: Rehman, A.
creator: Hassan, M.F.
creator: Naeem, B.
creator: Hooi, Y.K.
creator: Ali, M.S.
description: Internet of Vehicles (IoV) is the future of automated on-road vehicles; it emerged from the combination of two technologies Vehicular Ad Hoc Networks (VANETs) and the Internet of Things (IoT). Finding the shortest route has always been a challenge in road traffic, and many algorithms for the shortest path. However, the shortest route approach is not practical for real-world on-road traffic. Therefore, there is a requirement for an efficient path in terms of saving time. Ant Colony Optimization (ACO) is a good solution for the process of choosing the best path. Moreover, as ad hoc networks are constantly under security threats, secure communication is needed. A lot of work is under research in IoV security standards. Communication trust between the vehicles is one of the critical elements while assuring secure transmission. In Our research work, we have presented an algorithm to find the best path for IoV based on ACO and simultaneously ensure the message's integrity using trust. Based on the simulation, the preliminary experiment has shown positive results for algorithms. © 2021 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2021
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Rehman, A. and Hassan, M.F. and Naeem, B. and Hooi, Y.K. and Ali, M.S.  (2021) The best path selection using ant colony optimization and message trust in IoV.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126658836&doi=10.1109%2fICIC53490.2021.9692920&partnerID=40&md5=2c9e9559a2170aa7ab939d2f94ffdc11
relation: 10.1109/ICIC53490.2021.9692920
identifier: 10.1109/ICIC53490.2021.9692920