Distributed Edge Computing System for Vehicle Communication

Rinith Pakala, Niket Kathiriya, Hossein Haeri, Satya Maddipatla, Kshitij Jerath, Craig Beal, Sean Brennan, Cindy Chen

2023

Abstract

The development of communication technologies in edge computing has fostered progress across various applications, particularly those involving vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Enhanced infrastructure has improved data transmission network availability, promoting better connectivity and data collection from IoT devices. A notable IoT application is with the Intelligent Transportation System (ITS). IoT technology integration enables ITS to access a variety of data sources, including those pertaining to weather and road conditions. Real-time data on factors like temperature, humidity, precipitation, and friction contribute to improved decision-making models. Traditionally, these models are trained at the cloud level, which can lead to communication and computational delays. However, substantial advancements in cloud-to-edge computing have decreased communication relays and increased computational distribution, resulting in faster response times. Despite these benefits, the developments still largely depend on central cloud sources for computation due to restrictions in computational and storage capacity at the edge. This reliance leads to duplicated data transfers between edge servers and cloud application servers. Additionally, edge computing is further complicated by data models predominantly based on data heuristics. In this paper, we propose a system that streamlines edge computing by allowing computation at the edge, thus reducing latency in responding to requests across distributed networks. Our system is also designed to facilitate quick updates of predictions, ensuring vehicles receive more pertinent safety-critical model predictions. We will demonstrate the construction of our system for V2V and V2I applications, incorporating cloud-ware, middleware, and vehicle-ware levels.

Download


Paper Citation


in Harvard Style

Pakala R., Kathiriya N., Haeri H., Maddipatla S., Jerath K., Beal C., Brennan S. and Chen C. (2023). Distributed Edge Computing System for Vehicle Communication. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 398-405. DOI: 10.5220/0012088700003541


in Bibtex Style

@conference{data23,
author={Rinith Pakala and Niket Kathiriya and Hossein Haeri and Satya Maddipatla and Kshitij Jerath and Craig Beal and Sean Brennan and Cindy Chen},
title={Distributed Edge Computing System for Vehicle Communication},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={398-405},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012088700003541},
isbn={978-989-758-664-4},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Distributed Edge Computing System for Vehicle Communication
SN - 978-989-758-664-4
AU - Pakala R.
AU - Kathiriya N.
AU - Haeri H.
AU - Maddipatla S.
AU - Jerath K.
AU - Beal C.
AU - Brennan S.
AU - Chen C.
PY - 2023
SP - 398
EP - 405
DO - 10.5220/0012088700003541
PB - SciTePress