Closed liamsi closed 2 years ago
I would also add that in above's potential process, there is something that also needs to be considered:
Another dimension that isn't factored into this is that in the MVPs case: blocks were produced rapidly. Originally, even as fast as the machine could, usually < 1 sec. That is just loads of data from the pov of the dht. After adding the dummy-app there is an artificial delay to simulate execution and reaching consensus but it is also just a second. Note, this delay can be adjusted via a command line param. (ref: https://github.com/lazyledger/lazyledger-core/issues/383) The experiments in December/January where like one round of block production only. Which I think matters as well.
To actually come to a conclusion if this has anything to do with the NMT plugin, then this should also be factored in.
I don't think we need to continue these experiments but should instead use our node software to experiment with different sizes etc. I'm closing this for now (cc @Bidon15 @jbowen93).
Use this plugin when tackling #4 and #5.
An alternative to explicitly use the plugin, could be to actually spin up a lazyledger-app node and run the experiments directly on the embedded IPFS node using the API that will be introduced as an outcome of lazyledger/lazyledger-core#170. This approach could also be used via CI, e.g. triggered on each PR merged to master (in lazyledger-app/-core) or weekly, or, before every release. In the beginning, monthly and some way to manually trigger the CI run should be sufficient.
Copy & pasting a convo from discord related to figuring out why numbers differ with the MVP (ref: https://github.com/lazyledger/lazyledger-core/issues/377). Quoting @musalbas:
Adding this here as there is some overlap with 1. and this issue: LL nodes use the NMT plugin but not with a single data root.
Switching the experiments to just use a NMT plugin would need to happen first. Unless we keep this repo as simple as it currently is use something else to actually spin up LL nodes and do measurements.