Abstract
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, vehicles equipped with significantly powerful SCCSI capabilities are expected to 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, where SCCSI-empowered vehicles form a web of mobile sensors, a grid of mobile servers, a network of mobile routers, a fleet of mobile storage, and a set of AI toolboxes, to provide SCCSI services in smart cities. This paradigm is called Vehicle as a Service (VaaS). Towards this goal, this article first examines the potential use cases in smart cities and possible upgrades required for the transition from traditional vehicular ad hoc networks (VANETs) to VaaS. Then, the system architecture and use cases of the VaaS paradigm are comprehensively elaborated. Finally, the open problems of this paradigm and future research directions, including architectural design, service provisioning, incentive design, and security & privacy, are identified. This position paper is expected to pave the way towards developing a cost-effective and sustainable approach for smart cities and offer a complementary alternative for 5G and beyond.
| Original language | English |
|---|---|
| Pages (from-to) | 2048-2081 |
| Number of pages | 34 |
| Journal | IEEE Communications Surveys and Tutorials |
| Volume | 26 |
| Issue number | 3 |
| Early online date | 27 Feb 2024 |
| DOIs | |
| Publication status | Published - Jul 2024 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 1998-2012 IEEE.
Funding
This work was supported in part by the Hong Kong SAR Government under the Global STEM Professorship, and in part by the Hong Kong Jockey Club under JC STEM Lab of Smart City. The work of Xianhao Chen was supported in part by HKU IDS Research Seed Fund under Grant IDS-RSF2023-0012, and in part by HKU-SCF FinTech Academy RD Funding. The work of Yiqin Deng was supported in part by the National Natural Science Foundation of China under Grant 62301300. The work of Haichuan Ding was supported in part by the National Natural Science Foundation of China under Grant 92367201. The work of Haixia Zhang was supported in part by the Joint Funds of the National Science Foundation of China under Grant U22A2003.
Keywords
- cognitive radio networks
- edge computing
- edge intelligence
- Internet of Things (IoT)
- Internet of Vehicles (IoV)
- smart city
