The development of blockchain technologies has enabled the trustless execution of so-called smart contracts, i.e. programs that regulate the exchange of assets (e.g., cryptocurrency) between users. In a decentralized blockchain, the state of smart contracts is collaboratively maintained by a peer-to-peer network of mutually untrusted nodes, which collect from users a set of transactions (representing the required actions on contracts), and execute them in some order. Once this sequence of transactions is appended to the blockchain, the other nodes validate it, re-executing the transactions in the same order. The serial execution of transactions does not take advantage of the multi-core architecture of modern processors, so contributing to limit the throughput. In this paper we propose a true concurrent model of smart contracts execution. Based on this, we show how static analysis of smart contracts can be exploited to parallelize the execution of transactions.

A true concurrent model of smart contracts executions

Bartoletti M.
;
Murgia M.
2020-01-01

Abstract

The development of blockchain technologies has enabled the trustless execution of so-called smart contracts, i.e. programs that regulate the exchange of assets (e.g., cryptocurrency) between users. In a decentralized blockchain, the state of smart contracts is collaboratively maintained by a peer-to-peer network of mutually untrusted nodes, which collect from users a set of transactions (representing the required actions on contracts), and execute them in some order. Once this sequence of transactions is appended to the blockchain, the other nodes validate it, re-executing the transactions in the same order. The serial execution of transactions does not take advantage of the multi-core architecture of modern processors, so contributing to limit the throughput. In this paper we propose a true concurrent model of smart contracts execution. Based on this, we show how static analysis of smart contracts can be exploited to parallelize the execution of transactions.
2020
978-3-030-50028-3
978-3-030-50029-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/303186
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