A detailed study compared this innovative cluster mempool design with the existing Bitcoin Core architecture using 2023 data simulations. These simulations meticulously recorded all transactional and block data across the network, enabling a thorough comparison under uniform historical conditions. The methodology hinged on activating datalogging and simulation modes to replay network activities through Bitcoin Core's validation mechanisms, aiming to evaluate adjustments in mempool or consensus logic without real-time network engagement. This approach was designed to scrutinize changes with an emphasis on logging detail and maximizing mempool capacity, thereby reducing discrepancies unrelated to the mempool designs.

The prototype of the cluster mempool was specifically tested against traditional limits, allowing up to 100 transactions or 101 kilovirtual bytes per transaction cluster, which is distinct from the conventional mempool that restricts based on ancestor and descendant counts. The findings revealed minimal differences in the total number of transactions processed between the two implementations, despite differing rules for transaction acceptance and replacement. A notable feature of the cluster mempool was its mechanism for reprocessing transactions post-block delivery, indicating that transactions initially rejected due to cluster size limitations could eventually be accepted, thus minimally impacting user experience concerning transaction relay success rates.

Economic considerations were also addressed, comparing fee disparities between blocks produced in each simulation. The results suggested that the cluster mempool would not substantially alter miners' fee-based revenue. The study further examined Replace-By-Fee (RBF) policy variations, observing that the cluster mempool’s approach might prevent certain transactions that could reduce mempool efficiency, with little overall impact on transaction processing. It highlighted scenarios where the cluster mempool's criteria could exclude transactions deemed acceptable under current policies but potentially detrimental to mempool efficiency. This pointed out the necessity for ongoing optimization of mempool management strategies to align with changing network behaviors and demands.

In summary, the proposed cluster mempool design offers a theoretical enhancement in how transaction clusters and RBF rules are handled, unlikely to negatively influence network operations as per simulation outcomes. Although the practical benefits seem limited, they are nonetheless positive, hinting at a possibility for improved transaction processing without undermining the economic structure of the network.