A Survey on Directed Acyclic Graph-Based Blockchain in Smart Mobilityopen access
- Authors
- Bai, Yuhao; Lee, Soojin; Seo, Seung-Hyun
- Issue Date
- Feb-2025
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Keywords
- blockchain; DAG; directed acyclic graph; smart mobility
- Citation
- Sensors, v.25, no.4, pp 1 - 43
- Pages
- 43
- Indexed
- SCIE
SCOPUS
- Journal Title
- Sensors
- Volume
- 25
- Number
- 4
- Start Page
- 1
- End Page
- 43
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/122320
- DOI
- 10.3390/s25041108
- ISSN
- 1424-8220
1424-8220
- Abstract
- This systematic review examines the integration of directed acyclic graph (DAG)-based blockchain technology in smart mobility ecosystems, focusing on electric vehicles (EVs), robotic systems, and drone swarms. Adhering to PRISMA guidelines, we conducted a comprehensive literature search across Web of Science, Scopus, IEEE Xplore, and ACM Digital Library, screening 1248 records to identify 47 eligible studies. Our analysis demonstrates that DAG-based blockchain addresses critical limitations of traditional blockchains by enabling parallel transaction processing, achieving high throughput (>1000 TPS), and reducing latency (<1 s), which are essential for real-time applications like autonomous vehicle coordination and microtransactions in EV charging. Key technical challenges include consensus mechanism complexity, probabilistic finality, and vulnerabilities to attacks such as double-spending and Sybil attacks. This study identifies five research priorities: (1) standardized performance benchmarks, (2) formal security proofs for DAG protocols, (3) hybrid consensus models combining DAG with Byzantine fault tolerance, (4) privacy-preserving cryptographic techniques, and (5) optimization of feeless microtransactions. These advancements are critical for deploying robust, scalable DAG-based solutions in smart mobility, and fostering secure and efficient urban transportation networks. © 2025 by the authors.
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Collections - COLLEGE OF ENGINEERING SCIENCES > SCHOOL OF ELECTRICAL ENGINEERING > 1. Journal Articles

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