Content area

Abstract

Hybrid on/off-blockchain vehicle data management approaches have received a lot of attention in recent years. However, there are various technical challenges remained to deal with. In this paper we relied on real-world data from Austria to investigate the effects of connectivity on the transport of personal protective equipment. We proposed a three-step mechanism to process, simulate, and store/visualize aggregated vehicle datasets together with a formal pipeline process workflow model. To this end, we implemented a hybrid blockchain platform based on the hyperledger fabric and gluster file systems. The obtained results demonstrated efficiency and stability for both hyperledger fabric and gluster file systems and ability of the both on/off-blockchain mechanisms to meet the platform quality of service requirements

Details

1009240
Title
Hybrid On/Off Blockchain Approach for Vehicle Data Management, Processing and Visualization Exemplified by the ADAPT Platform
Publication title
arXiv.org; Ithaca
Publication year
2022
Publication date
Jul 26, 2022
Section
Computer Science
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2022-08-16
Milestone dates
2022-07-26 (Submission v1)
Publication history
 
 
   First posting date
16 Aug 2022
ProQuest document ID
2702669022
Document URL
https://www.proquest.com/working-papers/hybrid-on-off-blockchain-approach-vehicle-data/docview/2702669022/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2022. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2022-08-17
Database
ProQuest One Academic