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How Fast Are Ethereum Transactions, Really?
- Ethereum transactions are crucial for developers of blockchain-powered applications, known as ÐApps, for translating requests into smart contract transactions, with transaction speed linked to gas price paid.
- The study quantifies Ethereum transaction processing times, showing a median of 57 seconds with 90% processed within 8 minutes, indicating that higher gas prices result in faster processing times with diminishing returns.
- Accuracy of estimation services like Etherscan and EthGasStation varies, with Etherscan most accurate for cheap transactions and EthGasStation for regular, expensive, and very expensive ones.
- A linear regression model with one feature outperforms existing models for cheap transactions, aiding developers in making informed gas price decisions.
- Blockchain's transformative potential has led to high demand for blockchain expertise, as programmable blockchains like Ethereum host smart contracts and enable decentralized applications (ÐApps).
- Transaction processing times in Ethereum are influenced by gas price, blockchain workload, and miner nodes; appropriate gas price selection is crucial for balancing cost and user experience.
- Services like Etherscan and EthGasStation provide real-time estimates of processing times based on gas prices but lack clarity on internal workings, highlighting the need for empirical investigation.
- Developing accurate transaction processing time estimation models and insights into Ethereum transactions support developers in optimizing gas price choices for improved end-user experience.
- The study contributes by providing transaction processing time characterization, accuracy assessment of estimation services, and developing a model surpassing existing services' performance.
- The research aids ÐApp developers in decision-making regarding gas prices, and data analysis on Ethereum processing times offers valuable insights for those considering applications on this platform.
- The paper's structure includes sections on key concepts, motivating examples, transaction time computation, data collection, research findings, implications, related work, and conclusion.
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