Abstract
A blockchain is an open, distributed ledger that can record transactions between two parties in an efficient, verifiable, and permanent way. Once recorded in a block, the transaction data cannot be altered retroactively. Moreover, smart contracts can be put in place to ensure that any new data added to the blockchain respects the terms of an agreement between the involved parties. As such, the blockchain becomes the single source of truth for all stakeholders in the system.
These characteristics make blockchain technology especially useful in the context of Industry 4.0, distributed in nature, but with important requirements of trust and accountability among the large number of devices involved in the collaboration. In this chapter, we will see concrete scenarios where cyber-physical systems (CPSs) can benefit from blockchain technology, especially focusing on how blockchain works in practice, and which are the design and architectural trade-offs we should keep in mind when adopting this technology both for the design and operation of CPSs.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
Other methods for reaching consensus than PoW have been proposed—Proof of Stake (PoS), Deferred Proof of Stake (DPoS), or Practical Byzantine Fault Tolerance (PBFT), to name a few—but for the sake of simplicity, we will focus on PoW.
- 5.
- 6.
- 7.
All these gas fees are specified in the Ethereum Yellow Paper [32].
- 8.
- 9.
- 10.
- 11.
- 12.
- 13.
- 14.
International Maritime Organization, MSC.1/Circ.1475, 9 June 2014.
- 15.
- 16.
- 17.
- 18.
A deeper explanation of the concepts and metaclasses can be found in the original publication [23].
- 19.
- 20.
- 21.
- 22.
- 23.
- 24.
- 25.
- 26.
- 27.
- 28.
- 29.
- 30.
This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and Sweden, Austria, Czech Republic, Finland, France, Italy and Spain.
References
Baird, L.: The swirlds hashgraph consensus algorithm: Fair, fast, byzantine fault tolerance. Swirlds, Inc. Technical Report SWIRLDS-TR-2016 1 (2016)
Beller, M., Hejderup, J.: Blockchain-based software engineering. In: Sarma, A., Murta, L. (eds.) Proceedings of the 41st International Conference on Software Engineering: New Ideas and Emerging Results, ICSE (NIER) 2019, Montreal, QC, Canada, May 29-31, 2019. pp. 53–56. IEEE/ACM (2019). 10.1109/ICSE-NIER.2019.00022
Bernardi, S., Domínguez, J.L., Gómez, A., Joubert, C., Merseguer, J., Perez-Palacin, D., Requeno, J.I., Romeu, A.: A systematic approach for performance assessment using process mining - An industrial experience report. Empir. Softw. Eng. 23(6), 3394–3441 (2018). 10.1007/s10664-018-9606-9
Blinder, A.S.: Offshoring: the next industrial revolution? Foreign affairs pp. 113–128 (2006)
Braeken, A., Liyanage, M., Kanhere, S.S., Dixit, S.: Blockchain and cyberphysical systems. Computer 53(09), 31–35 (sep 2020). 10.1109/MC.2020.3005112
Brambilla, M., Cabot, J., Wimmer, M.: Model-Driven Software Engineering in Practice, Second Edition. Synthesis Lectures on Software Engineering, Morgan & Claypool Publishers (2017). 10.2200/S00751ED2V01Y201701SWE004
Brunelière, H., Burger, E., Cabot, J., Wimmer, M.: A feature-based survey of model view approaches. Software and Systems Modeling 18(3), 1931–1952 (2019). 10.1007/s10270-017-0622-9
Casale, G., et al.: DICE: quality-driven development of data-intensive cloud applications. In: Gray, J., Chechik, M., Kulkarni, V., Paige, R.F. (eds.) 7th IEEE/ACM International Workshop on Modeling in Software Engineering, MiSE 2015, Florence, Italy, May 16-17, 2015. pp. 78–83. IEEE Computer Society (2015). 10.1109/MiSE.2015.21
Cataldo, M., Herbsleb, J.D., Carley, K.M.: Socio-technical congruence: a framework for assessing the impact of technical and work dependencies on software development productivity. In: Rombach, H.D., Elbaum, S.G., Münch, J. (eds.) Proceedings of the Second International Symposium on Empirical Software Engineering and Measurement, ESEM 2008, October 9-10, 2008, Kaiserslautern, Germany. pp. 2–11. ACM (2008). 10.1145/1414004.1414008
Falazi, G., Hahn, M., Breitenbücher, U., Leymann, F.: Modeling and execution of blockchain-aware business processes. SICS Softw.-Intensive Cyber Phys. Syst. 34(2-3), 105–116 (2019). 10.1007/s00450-019-00399-5
Fowler, M.: Analysis Patterns: Reusable Objects Models. Addison-Wesley Longman Publishing Co., Inc., USA (1996)
Fowler, M.: Patterns of Enterprise Application Architecture. Addison-Wesley Longman Publishing Co., Inc., USA (2002)
Gil, M., Joubert, C., Torres, I.: Model-driven engineering IDE for quality assessment of data-intensive applications. In: Binder, W., Cortellessa, V., Koziolek, A., Smirni, E., Poess, M. (eds.) Companion Proceedings of the 8th ACM/SPEC on International Conference on Performance Engineering, ICPE 2017, L’Aquila, Italy, April 22–26, 2017. pp. 173–174. ACM (2017). 10.1145/3053600.3053633
Härer, F., Fill, H.: Decentralized attestation of conceptual models using the ethereum blockchain. In: Becker, J., Novikov, D. (eds.) 21st IEEE Conference on Business Informatics, CBI 2019, Moscow, Russia, July 15–17, 2019, Volume 1 – Research Papers. pp. 104–113. IEEE (2019). 10.1109/CBI.2019.00019
Harris, J.D., Waggoner, B.: Decentralized and collaborative ai on blockchain. In: 2019 IEEE International Conference on Blockchain (Blockchain). pp. 368–375. IEEE Computer Society, Los Alamitos, CA, USA (jul 2019). 10.1109/Blockchain.2019.00057
Izquierdo, J.L.C., Cabot, J.: Collaboro: a collaborative (meta) modeling tool. PeerJ Comput. Sci. 2, e84 (2016). 10.7717/peerj-cs.84
Larman, C.: Applying UML and Patterns: An Introduction to Object-Oriented Analysis and Design and Iterative Development (3rd Edition). Prentice Hall PTR, USA (2004)
Lee, E.A.: Cyber physical systems: Design challenges. In: 2008 11th IEEE International Symposium on Object and Component-Oriented Real-Time Distributed Computing (ISORC). pp. 363–369. IEEE (2008)
Lehnert, S., Farooq, Q., Riebisch, M.: A taxonomy of change types and its application in software evolution. In: IEEE 19th International Conference and Workshops on Engineering of Computer-Based Systems (ECBS). pp. 98–107. IEEE Computer Society (2012). 10.1109/ECBS.2012.9
Martínez, S., Gérard, S., Cabot, J.: Robust hashing for models. In: Wasowski, A., Paige, R.F., Haugen, Ø. (eds.) Proceedings of the 21th ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2018, Copenhagen, Denmark, October 14–19, 2018. pp. 312–322. ACM (2018). 10.1145/3239372.3239405
Nakamoto, S.: Bitcoin: A Peer-to-Peer Electronic Cash System, https://bitcoin.org/bitcoin.pdf
Narayanan, A., Bonneau, J., Felten, E., Miller, A., Goldfeder, S.: Bitcoin and cryptocurrency technologies: a comprehensive introduction. Princeton University Press (2016)
Olivé, A.: The conceptual schema of ethereum. In: Dobbie, G., Frank, U., Kappel, G., Liddle, S.W., Mayr, H.C. (eds.) Conceptual Modeling. pp. 418–428. Springer International Publishing, Cham (2020)
Pelz-Sharpe, A.: Enterprise blockchain – market forecast & scenarios 2019-2024 (2019), https://www.deep-analysis.net/wp-content/uploads/2019/08/DA-190812-Ent-Blockchain-forecast.pdf
Rocha, H., Ducasse, S.: Preliminary steps towards modeling blockchain oriented software. In: 1st IEEE/ACM International Workshop on Emerging Trends in Software Engineering for Blockchain, WETSEB@ICSE 2018, Gothenburg, Sweden, May 27–June 3, 2018. pp. 52–57. ACM (2018), http://ieeexplore.ieee.org/document/8445060
Rogers, E.M.: Diffusion of innovations. Simon and Schuster (2010)
Ruoti, S., Kaiser, B., Yerukhimovich, A., Clark, J., Cunningham, R.K.: Blockchain technology: what is it good for? Commun. ACM 63(1), 46–53 (2020). 10.1145/3369752
Samaniego, M., Jamsrandorj, U., Deters, R.: Blockchain as a service for iot. In: 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). pp. 433–436 (2016)
Szabo, N.: Formalizing and securing relationships on public networks. First Monday 2(9) (Sep 1997). 10.5210/fm.v2i9.548
UK Government, O.f.S.: Distributed Ledger Technology: beyond block chain. Tech. rep., UK Government (2016)
United Nations: Blockchain in Trade Facilitation: Sectoral challenges and examples (ECE/TRADE/C/CEFACT/2019/INF.3) (2019), https://unece.org/fileadmin/DAM/cefact/cf_plenary/2019_plenary/CEFACT_2019_INF03.pdf
Wood, G.: Ethereum: A secure decentralised generalised transaction ledger (41c1837 – 2021-02-14) (2021), https://ethereum.github.io/yellowpaper/paper.pdf
Acknowledgements
This work has received support from the AIDOaRt project, funded by the ECSEL Joint Undertaking under grant agreement No. 101007350.Footnote 30
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature
About this chapter
Cite this chapter
Gómez, A., Joubert, C., Cabot, J. (2023). Blockchain Technologies in the Design and Operation of Cyber-Physical Systems. In: Vogel-Heuser, B., Wimmer, M. (eds) Digital Transformation. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-65004-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-662-65004-2_9
Published:
Publisher Name: Springer Vieweg, Berlin, Heidelberg
Print ISBN: 978-3-662-65003-5
Online ISBN: 978-3-662-65004-2
eBook Packages: Computer ScienceComputer Science (R0)