Graph Attention Network-based Block Propagation with Optimal AoI and Reputation in Web 3.0
arxiv(2024)
摘要
Web 3.0 is recognized as a pioneering paradigm that empowers users to
securely oversee data without reliance on a centralized authority. Blockchains,
as a core technology to realize Web 3.0, can facilitate decentralized and
transparent data management. Nevertheless, the evolution of blockchain-enabled
Web 3.0 is still in its nascent phase, grappling with challenges such as
ensuring efficiency and reliability to enhance block propagation performance.
In this paper, we design a Graph Attention Network (GAT)-based reliable block
propagation optimization framework for blockchain-enabled Web 3.0. We first
innovatively apply a data-freshness metric called age of information to measure
block propagation efficiency in public blockchains. To achieve the reliability
of block propagation, we introduce a reputation mechanism based on the
subjective logic model, including the local and recommended opinions to
calculate the miner reputation value. Moreover, considering that the GAT
possesses the excellent ability to process graph-structured data, we utilize
the GAT with reinforcement learning to obtain the optimal block propagation
trajectory. Numerical results demonstrate that the proposed scheme exhibits the
most outstanding block propagation efficiency and reliability compared with
traditional routing algorithms.
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