CRDBDCNov 11, 2019

Cost-Effective Data Feeds to Blockchains via Workload-Adaptive Data Replication

arXiv:1911.04078v3
Originality Incremental advance
AI Analysis

This work addresses cost reduction for blockchain data feeds, which is crucial for applications like stablecoins, but it is incremental as it builds on existing data placement methods by adding dynamic adaptation.

The paper tackles the problem of high blockchain Gas costs for data feeds by designing GRuB, a workload-adaptive data replication system that dynamically replicates data between blockchain and off-chain storage, achieving Gas savings of 10% to 74% compared to static baselines.

Feeding external data to a blockchain, a.k.a. data feed, is an essential task to enable blockchain interoperability and support emerging cross-domain applications, notably stablecoins. Given the data-intensive feeds in real life (e.g., high-frequency price updates) and the high cost in using blockchain, namely Gas, it is imperative to reduce the Gas cost of data feeds. Motivated by the constant-changing workloads in finance and other applications, this work focuses on designing a dynamic, workload-aware approach for cost effectiveness in Gas. This design space is understudied in the existing blockchain research which has so far focused on static data placement. This work presents GRuB, a cost-effective data feed that dynamically replicates data between the blockchain and an off-chain cloud storage. GRuB's data replication is workload-adaptive by monitoring the current workload and making online decisions w.r.t. data replication. A series of online algorithms are proposed that achieve the bounded worst-case cost in blockchain's Gas. GRuB runs the decision-making components on the untrusted cloud off-chain for lower Gas costs, and employs a security protocol to authenticate the data transferred between the blockchain and cloud. The overall GRuB system can autonomously achieve low Gas costs with changing workloads. We built a GRuB prototype functional with Ethereum and Google LevelDB, and supported real applications in stablecoins. Under real workloads collected from the Ethereum contract-call history and mixed workloads of YCSB, we systematically evaluate GRuB's cost which shows a saving of Gas by 10% ~ 74%, with comparison to the baselines of static data-placement.

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