MSTDB: A Hybrid Storage-Empowered Scalable Semantic Blockchain Database

Enyuan Zhou, Zicong Hong, Yang Xiao, Dongxiao Zhao, Qingqi Pei, Song Guo, Rajendra Akerkar

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)

Abstract

Blockchain has been regarded as a trusted carrier for distributed data storage. With large volumes of valuable data stored on blockchain, data query has become a major requirement. However, the existing blockchains do not provide efficient query functionality because of their deep-rooted chain structure. Blockchain database is a new direction that constructs index on top of blockchain to provide rich query functionalities. The existing works are either insecure because the query process separates from the blockchain consensus, or inscalable because all the data needs to be stored in the block. In this paper, we propose a novel semantic blockchain database called MSTDB. We design a hybrid on/off chain blockchain storage architecture in which the majority of blockchain storage is offloaded to the off-chain storage and a novel index structure named Merkle Semantic Trie (MST) is designed to be a secure and semantic bridge between on- and off-chain. Based on MST, MSTDB provides a variety of semantic query functions including multi-keyword query, range query, Top-K query, and cross-chain query. To improve the performance further, we design some index compression and query preprocessing techniques for MSTDB. Extensive experiments demonstrate the effectiveness and efficiency of our blockchain database.

Original languageEnglish
Pages (from-to)8228 - 8244
Number of pages17
JournalIEEE Transactions on Knowledge and Data Engineering
DOIs
Publication statusPublished - Nov 2022

Keywords

  • Blockchain database
  • Blockchains
  • Costs
  • data sharing
  • Databases
  • distributed query
  • index
  • Indexes
  • Scalability
  • Semantics
  • Supply chains

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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