Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/132217
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Type: Conference paper
Title: Anatomy, concept, and design space of blockchain networks
Author: Tran, N.K.
Babar, M.A.
Citation: Proceedings of the IEEE 17th International Conference on Software Architecture (ICSA 2020), 2020, pp.125-134
Publisher: IEEE
Publisher Place: online
Issue Date: 2020
ISBN: 9781728146591
Conference Name: IEEE International Conference on Software Architecture (ICSA) (2 Nov 2020 - 6 Nov 2020 : Salvador, Brazil)
Statement of
Responsibility: 
Nguyen Khoi Tran, M. Ali Babar
Abstract: Blockchain technologies have been increasingly adopted by enterprises to increase operational efficiency and enable new business models. These enterprise blockchain applications generally run on dedicated blockchain networks due to regulations and security requirements. The design process of these networks involves many decisions and trade-offs that impact security, governance, and performance of applications that run on them. The challenge is further exacerbated by the lack of a common architecture and concept map to communicate about blockchain networks, as blockchain technologies tend to use different concepts and architecture. This paper presents a concept map, an anatomy and the principal dimensions of the design space of blockchain networks. We applied the proposed design space in a case study about designing and deploying a blockchain network for an ad-hoc IoT infrastructure. We found that the design space brought structure to the design process and the analysis of design alternatives. The presented concept map, anatomy and design space are intended to help improve the blockchain network design practice and lay a foundation for future research on the design process and deployment automation of blockchain networks.
Keywords: Blockchain; Architecture; Design Space; Concept; Design
Rights: ©2020 IEEE
DOI: 10.1109/ICSA47634.2020.00020
Published version: https://ieeexplore.ieee.org/xpl/conhome/9094148/proceeding
Appears in Collections:Computer Science publications

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