Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities

Bibliographic Details
Title: Vehicle as a Service (VaaS): Leverage Vehicles to Build Service Networks and Capabilities for Smart Cities
Authors: Chen, Xianhao, Deng, Yiqin, Ding, Haichuan, Qu, Guanqiao, Zhang, Haixia, Li, Pan, Fang, Yuguang
Publication Year: 2023
Collection: Computer Science
Subject Terms: Computer Science - Networking and Internet Architecture, Computer Science - Distributed, Parallel, and Cluster Computing
More Details: Smart cities demand resources for rich immersive sensing, ubiquitous communications, powerful computing, large storage, and high intelligence (SCCSI) to support various kinds of applications, such as public safety, connected and autonomous driving, smart and connected health, and smart living. At the same time, it is widely recognized that vehicles such as autonomous cars, equipped with significantly powerful SCCSI capabilities, will become ubiquitous in future smart cities. By observing the convergence of these two trends, this article advocates the use of vehicles to build a cost-effective service network, called the Vehicle as a Service (VaaS) paradigm, where vehicles empowered with SCCSI capability form a web of mobile servers and communicators to provide SCCSI services in smart cities. Towards this direction, we first examine the potential use cases in smart cities and possible upgrades required for the transition from traditional vehicular ad hoc networks (VANETs) to VaaS. Then, we will introduce the system architecture of the VaaS paradigm and discuss how it can provide SCCSI services in future smart cities, respectively. At last, we identify the open problems of this paradigm and future research directions, including architectural design, service provisioning, incentive design, and security & privacy. We expect that this paper paves the way towards developing a cost-effective and sustainable approach for building smart cities.
Comment: 32 pages, 11 figures
Document Type: Working Paper
Access URL: http://arxiv.org/abs/2304.11397
Accession Number: edsarx.2304.11397
Database: arXiv
More Details
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