Off-Chain Execution of IoT Smart Contracts

Cacciagrano, Diletta; Corradini, Flavio; Mazzante, Gianmarco; Mostarda, Leonardo; Sestili, Davide

doi:10.1007/978-3-030-75075-6_50

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…Our design is based on the protocol described in Cacciagrano et al (2021), called DIVERSITY. As represented schematically in Figure 1, DIVERSITY is a second-layer decentralized network that offers off-chaining computation of smart contracts, regardless of which blockchain platform is used.…”

Section: Data Infrastructurementioning

confidence: 99%

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Off-chain trading for micro grid systems

Marcozzi

Mostarda²,

Cacciagrano³

2022

Front. Blockchain

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As micro grids and blockchain gained the interest and attention of both academia and the industry, the interaction between the two technologies seems inevitable. However, there are challenges to overcome in order to actually realize the integration between micro grids and blockchains. In this article, we review the solutions proposed to enhance micro grids with blockchains. We discuss the scalability challenges and the opportunities derived from the off-chaining computing techniques. In this context, we draft a design to implement a micro grid-based peer-to-peer local energy market, powered by an off-chain computing protocol called DIVERSITY. DIVERSITY aims to shift the computational burden from a main blockchain to an intermediate layer of nodes, aggregating data and executing smart contracts off-chain. We simulate different data logging approaches, and it is found that DIVERSITY allows an actual saving on fees and power consumption derived from using a public blockchain platform, such as Ethereum, in order to assure a truly decentralized renewable energy distribution at a lower cost.

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Section: Data Infrastructurementioning

confidence: 99%

“…Simulation settings, that is, virtual machines used and number of nodes composing the blockchain, are borrowed from Cacciagrano et al (2021) since the only difference in simulation is the artificial dataset.…”

Section: Simulation Settingsmentioning

confidence: 99%