RollStore: Hybrid Onchain-Offchain Data Indexing for Blockchain Applications

The interest in building blockchain Decentralized Applications (DApps) has been growing over the past few years. DApps are implemented as smart contracts which are programs that are maintained by a blockchain network. Building DApps, however, faces many challenges—most notably the performance and monetary overhead of writing to blockchain smart contracts. To overcome this challenge, many DApp developers have explored utilizing <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off-chain</i> resources—nodes outside of the blockchain network—to offload part of the processing and storage. In this paper, we propose RollStore, a data indexing solution for hybrid onchain-offchain DApps. RollStore provides efficiency in terms of reduced cost and latency, as well as security in terms of tolerating Byzantine (i.e., malicious) off-chain nodes. RollStore achieves this by: (1) a three-stage commitment strategy where each stage represents a point in a performance-security trade-off—i.e., the first stage is fast but less secure while the last stage is slower but more secure. (2) utilizing zero-knowledge (zk) proofs to enable the on-chain smart contract to verify off-chain operations with a small cost. (3) Combining Log-Structured Merge (LSM) trees and Merkle Mountain Range (MMR) trees to efficiently enable both access and verification of indexed data. We experimentally evaluate the cost and performance benefits of RollStore while comparing with BlockchainDB and BigChainDB.

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Publication Details

Journal
IEEE Transactions on Knowledge and Data Engineering
Published
2024-08-12
DOI
https://doi.org/10.1109/tkde.2024.3436514
Citations
9
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
7.01
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article

RollStore: Hybrid Onchain-Offchain Data Indexing for Blockchain Applications

Lin Qi, Faisal Nawab, Binbin Gu
9 citations
IEEE Transactions on Knowledge and Data Engineering
Blockchain Technology Applications and Security
7.01
article

RollStore: Hybrid Onchain-Offchain Data Indexing for Blockchain Applications

Lin Qi, Faisal Nawab, Binbin Gu
article en
9 citations

Abstract

The interest in building blockchain Decentralized Applications (DApps) has been growing over the past few years. DApps are implemented as smart contracts which are programs that are maintained by a blockchain network. Building DApps, however, faces many challenges—most notably the performance and monetary overhead of writing to blockchain smart contracts. To overcome this challenge, many DApp developers have explored utilizing <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off-chain</i> resources—nodes outside of the blockchain network—to offload part of the processing and storage. In this paper, we propose RollStore, a data indexing solution for hybrid onchain-offchain DApps. RollStore provides efficiency in terms of reduced cost and latency, as well as security in terms of tolerating Byzantine (i.e., malicious) off-chain nodes. RollStore achieves this by: (1) a three-stage commitment strategy where each stage represents a point in a performance-security trade-off—i.e., the first stage is fast but less secure while the last stage is slower but more secure. (2) utilizing zero-knowledge (zk) proofs to enable the on-chain smart contract to verify off-chain operations with a small cost. (3) Combining Log-Structured Merge (LSM) trees and Merkle Mountain Range (MMR) trees to efficiently enable both access and verification of indexed data. We experimentally evaluate the cost and performance benefits of RollStore while comparing with BlockchainDB and BigChainDB.

IEEE Transactions on Knowledge and Data EngineeringVol. 36(12)
University of California, Irvine (US)
Openalex Percentile: Top 3%
Blockchain Technology Applications and Security
7.01
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RollStore: Hybrid Onchain-Offchain Data Indexing for Blockchain Applications — Lin Qi, Faisal Nawab, et al. · IEEE Transactions on Knowledge and Data Engineering (2024) | TGRS Research Map | TGRS