Meijers, James, Dharma Putra, Guntur, Kotsialou, Grammateia, Kanhere, Salil S. and Veneris, Andreas (2021) Cost-effective blockchain-based IoT data marketplaces with a credit invariant. In: IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2021. IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2021. IEEE. ISBN 9781665435789
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Abstract
Billions of Internet of Things (IoT) devices deployed today collect massive amounts of potentially valuable data. To efficiently utilize this data, markets must be developed where data can be traded in real time. Blockchain technology offers a potential platform for these types of markets. However, previous proposals using blockchain technology either require trusted third parties such as data brokers, or necessitate a large number of on-chain transactions to operate, incurring excessive overhead costs. This paper proposes a trustless data trading system that minimizes both the risk of fraud and the number of transactions performed on chain. In this system, data producers and consumers come to binding agreements while trading data off chain and they only settle on chain when a deposit or withdrawal of funds is required. A credit mechanism is also developed to further reduce the incurred fees. Additionally, the proposed marketplace is benchmarked on a private Ethereum network running on a lab-scale testbed and the proposed credit system is simulated so to analyze its risks and benefits.
Item Type: | Book Section |
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Official URL: | https://ieeexplore.ieee.org/xpl/conhome/9460986/pr... |
Additional Information: | © 2021 IEEE |
Divisions: | Mathematics |
Subjects: | Q Science > QA Mathematics > QA76 Computer software H Social Sciences > HG Finance T Technology |
Date Deposited: | 14 Jan 2022 12:15 |
Last Modified: | 30 Nov 2024 08:03 |
URI: | http://eprints.lse.ac.uk/id/eprint/113437 |
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