  Transaction fees are a crucial revenue source for miners in public and
consortium blockchains. However, while public blockchains have additional
revenue streams, transaction fees serve as the primary income for miners in
consortium blockchains formed by various financial institutions. These miners
allocate different levels of computing resources to process transactions and
earn corresponding fees. Nonetheless, relying solely on transaction fees can
lead to significant volatility and encourage non-standard mining behaviors,
thereby posing threats to the blockchain's security and integrity. Despite
previous attempts to mitigate the impact of transaction fees on illicit mining
behaviors, a comprehensive solution to this vulnerability is yet to be
established. To address this gap, we introduce a novel approach that leverages
Dynamic Transaction Storage (DTS) strategies to effectively minimize block
incentive volatility. Our solution implements a Verkle tree-based storage
mechanism to reduce bandwidth consumption. Moreover, to configure the DTS
strategies, we evaluate several optimization algorithms and formulate the
challenge as a Vehicle Routing Problem. Our experiments conducted using
historical transactions from Bitcoin and remittance data from the Industrial
and Commercial Bank of China reveal that the strategy focusing on time-based
transaction incorporation priority, while excluding a designated space for
small-fee transactions, as discovered by the gradient-based optimizer
algorithm, proves most effective in reducing volatility. Hence, the DTS
strategy can sustain stable block incentives irrespective of transaction types
or user bidding behavior. Furthermore, the inclusion of higher-fee
transactions, often smaller in size, can alleviate propagation delays and the
occurrence of forks.
