Effect of Miner Incentive on the Confirmation Time of Bitcoin Transactions

Gebraselase, Befekadu G.; Helvik, Bjarne E.; Jiang, Yuming

doi:10.1109/blockchain53845.2021.00079

Cited by 1 publication

(1 citation statement)

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“…A model was established based on modern machine learning technology [18] to predict the approximate interval range in which miner nodes accept transactions and include them in blocks. Research [19] proposed a model to study the impact of different miner incentives on Bitcoin transaction confirmation time, such as fee-by-byte, fee-based, and first-in-first-out. Analysis indicates that even with larger block sizes, transactions with lower fees wait longer.…”

Section: Related Workmentioning

confidence: 99%

A Novel High-Efficiency Transaction Verification Scheme for Blockchain Systems

Zhang,

Zhou,

Wang

et al. 2024

CMES

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Blockchain can realize the reliable storage of a large amount of data that is chronologically related and verifiable within the system. This technology has been widely used and has developed rapidly in big data systems across various fields. An increasing number of users are participating in application systems that use blockchain as their underlying architecture. As the number of transactions and the capital involved in blockchain grow, ensuring information security becomes imperative. Addressing the verification of transactional information security and privacy has emerged as a critical challenge. Blockchain-based verification methods can effectively eliminate the need for centralized third-party organizations. However, the efficiency of nodes in storing and verifying blockchain data faces unprecedented challenges. To address this issue, this paper introduces an efficient verification scheme for transaction security. Initially, it presents a node evaluation module to estimate the activity level of user nodes participating in transactions, accompanied by a probabilistic analysis for all transactions. Subsequently, this paper optimizes the conventional transaction organization form, introduces a heterogeneous Merkle tree storage structure, and designs algorithms for constructing these heterogeneous trees. Theoretical analyses and simulation experiments conclusively demonstrate the superior performance of this scheme. When verifying the same number of transactions, the heterogeneous Merkle tree transmits less data and is more efficient than traditional methods. The findings indicate that the heterogeneous Merkle tree structure is suitable for various blockchain applications, including the Internet of Things. This scheme can markedly enhance the efficiency of information verification and bolster the security of distributed systems.

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Section: Related Workmentioning

confidence: 99%