PEEP: A Parallel Execution Engine for Permissioned Blockchain Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Unlike blockchain systems in public settings, the stricter trust model in permissioned blockchain opens an opportunity for pursuing higher throughput. Recently, as the consensus protocols are developed significantly, the existing serial execution manner of transactions becomes a key factor in limiting overall performance. However, it is not easy to extend the concurrency control protocols, widely used in database systems, to blockchain systems. In particular, there are two challenges to achieve parallel execution of transactions in blockchain as follows: (i) the final results of different replicas may diverge since most protocols just promise the effect of transactions equivalent to some serial order but this order may vary for every concurrent execution; and (ii) almost all state trees that are used to manage states of blockchain do not support fast concurrent updates. In the view of above challenges, we propose a parallel execution engine called PEEP, towards permissioned blockchain systems. Specifically, PEEP employs a deterministic concurrency mechanism to obtain a predetermined serial order for parallel execution, and offers parallel update operations on state tree, which can be implemented on any radix tree with Merkle property. Finally, the extensive experiments show that PEEP outperforms existing serial execution greatly.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 26th International Conference, DASFAA 2021, Proceedings
EditorsChristian S. Jensen, Ee-Peng Lim, De-Nian Yang, Wang-Chien Lee, Vincent S. Tseng, Vana Kalogeraki, Jen-Wei Huang, Chih-Ya Shen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages341-357
Number of pages17
ISBN (Print)9783030731991
DOIs
StatePublished - 2021
Event26th International Conference on Database Systems for Advanced Applications, DASFAA 2021 - Taipei, Taiwan, Province of China
Duration: 11 Apr 202114 Apr 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12683 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Conference on Database Systems for Advanced Applications, DASFAA 2021
Country/TerritoryTaiwan, Province of China
CityTaipei
Period11/04/2114/04/21

Keywords

  • Blockchain
  • Execution optimization
  • Permissioned

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