Increasing popularity of trading digital assets can lead to significant delays in Blockchain networks when processing transactions. When transaction fees become miners' primary revenue, an imbalance in reward may lead to miners adopting deviant mining strategies. Scaling the block capacity is one of the potential approaches to alleviate the problem. To address this issue, this paper reviews and evaluates six state-of-the-art compression protocols for Blockchains. Specifically, we designed a Monte Carlo simulation to simulate two of the six protocols to observe their compression performance under larger block capacities. Furthermore, extensive simulation experiments were conducted to observe the mining behaviour when the block capacity is increased. Experimental results reveal an interesting trade-off between volatility and scalability. When the throughput is higher than a critical point, it worsens the volatility and threatens Blockchain security. In the experiments, we further analyzed the relationship between volatility and scalability properties with respect to the distribution of transaction values. Based on the analysis results, we proposed the recommended maximum block size for each protocol. At last, we discuss the further improvement of the compression protocols.

翻译：数字资产交易日益普及可能导致区块链网络在处理交易时产生显著延迟。当交易费用成为矿工主要收入来源时，收益失衡可能促使矿工采取异常挖矿策略。扩大区块容量是缓解该问题的潜在途径之一。为解决这一问题，本文对六种最先进的区块链压缩协议进行了综述与评估。具体而言，我们设计了蒙特卡洛模拟来仿真其中两种协议在大区块容量下的压缩性能。此外，通过大量仿真实验观察了区块容量增大时的挖矿行为。实验结果表明，波动性与可扩展性之间存在有趣的权衡关系：当吞吐量超过临界点时，波动性恶化并威胁区块链安全性。在实验中，我们进一步分析了波动性与可扩展性属性与交易价值分布的关系。基于分析结果，我们针对每种协议提出了推荐的最大区块容量。最后，讨论了压缩协议的进一步改进方向。