
Departmental Papers (CIS)
Date of this Version
7-2018
Document Type
Conference Paper
Recommended Citation
Deepak Gangadharan, Oleg Sokolsky, Insup Lee, BaekGyu Kim, Chung-Wei Lin, and Shinichi Shiraishi, "Bandwidth Optimal Data/Service Delivery for Connected Vehicles via Edges", IEEE International Conference on Cloud Computing (CLOUD 2018) . July 2018.
Abstract
The paradigm of connected vehicles is fast gaining lot of attraction in the automotive industry. Recently, a lot of technological innovation has been pushed through to realize this paradigm using vehicle to cloud (V2C), infrastructure (V2I) and vehicle (V2V) communications. This has also opened the doors for efficient delivery of data/service to the vehicles via edge devices that are closer to the vehicles. In this work, we propose an optimization framework that can be used to deliver data/service to the connected vehicles such that a bandwidth cost objective is optimized. For the first time, we also integrate a vehicle flow model in the optimization framework to model the traffic flow in the coverage area of the edges. Using the optimization framework, we study the variation of the optimal bandwidth cost for varying problem sizes and vehicle flow model parameter values for both data and service delivery.
Subject Area
CPS Auto, CPS Internet of Things
Publication Source
IEEE International Conference on Cloud Computing (CLOUD 2018)
Copyright/Permission Statement
© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords
connected vehicles, edge computing, V2C, V2I, data delivery, service delivery, bandwidth cost
Date Posted: 09 July 2018
This document has been peer reviewed.
Comments
IEEE International Conference on Cloud Computing (CLOUD 2018), San Francisco, CA, USA, July 2 - 7, 2018