ACO-based Approach on Dynamic MSMD Routing in IoV Environment

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초록

Recently, the advance of the Internet of Things (IoT) and wireless communication technology, specifically Vehicles-to-Everything (V2X), makes a huge contribution to road transportation. The fully connected and autonomous system of road transportation can be basically made in practice by integrating V2X with a current autonomous vehicle. In this paper, we focus on dynamic traffic routing for IoT-based connected vehicles. First, we define the problem of identifying the best paths for all vehicles with different sources and different destinations, or multi-source multi-destination (MSMD) traffic flows. Then, Ant Colony Optimization (ACO)-based approach with coloring ants concept is proposed to solve the problem in a decentralized and self decision-making manner. The simulation is carried out on the NetLogo platform with a multi-intersection scenario. The simulation results show that the ACO-based routing approach outperforms the non-ACO-based approach in terms of average traveling time and the number of vehicles passing metrics.

키워드

Ant Colony Optimization; Connected Vehicles; Dynamic Routing; IoV; MSMD; ANT COLONY; OPTIMIZATION; INTERNET; VEHICLES; THINGS
제목
ACO-based Approach on Dynamic MSMD Routing in IoV Environment
저자
Nguyen, Tri-Hai; Jung, Jason J.
DOI
10.1109/IE49459.2020.9154927
발행일
2020-07
유형
Proceedings Paper
저널명
PROCEEDINGS OF THE 2020 16TH INTERNATIONAL CONFERENCE ON INTELLIGENT ENVIRONMENTS (IE)
페이지
68 ~ 73