Previous research presented a solution for the pathfinding problem in a privacy-aware payment channel network. The proposed solution includes a rebalancing protocol which the nodes of the network should follow to achieve a higher balancedness for both themselves and the entire network. These payment channel networks are decentralised by nature and protocol changes can not be forced upon the node operators. Therefore, the question arises on how effective this protocol change will be assuming only partial participation of nodes.

The proposed rebalancing algorithm is simulated in Python. The channels and nodes from the real Lightning Netwerk were used to reconstruct a graph as realistic as possible. Then the simulation was adapted to run the algorithm with a set of nodes only. Different levels of participation were evaluated. Furthermore, various selection methods for the participating nodes were defined and simulated. In order to measure the ability to route payments, three performance measures were defined. In each simulation those measures are calculated during the rebalancing and in the end.

The results show how the participation levels affect the effectiveness of the protocol change. It becomes evident what levels are needed to record an improvement in the performance measures. The selection strategy that sorts the nodes by their importance has shown the heterogenity of the network. Few of the most central nodes are crucial to facilitate rebalancing. Their absence leads to a significant drop in rebalancing activity and balance of the network. Furthermore, the fit of the Gini score as a proxy for the balance of a network has been confirmed. However, it was shown that other factors are influencing the balance which are not covered by the Gini score. These insights will help Lightning Network developers to make decisions about whether such a protocol should be adopted or not. It helps to estimate the expected improvement from such a change under certain conditions. The simulation code is made publicly available. Hence, other simulations within a payment channel network are easily developed with the code as a basis.