Dave Hudson [d...@hashingit.com] wrote: > A damping-based design would seem like the obvious choice (I can think of a > few variations on a theme here, but most are found in the realms of control > theory somewhere). The problem, though, is working working out a timeframe > over which to run the derivative calculations.
>From a measurement theory perspective this is straightforward. Each block is a measurement, and error propagation can be performed to derive an error on the derivatives. The statistical theory of Bitcoin's block timing is known as a Poisson Point Process: https://en.wikipedia.org/wiki/Poisson_point_process or temporal point process. If you google those plus "estimation" you'll find a metric shit-ton of literature on how to handle this. > The problem is the measurement of the hashrate, which is pretty inaccurate at > best because even 2016 events isn't really enough (with a completely constant > hash rate running indefinitely we'd see difficulty swings of up to +/- 5% even > with the current algorithm). In order to meaningfully react to a major loss > of hashing we'd still need to be considering a window of probably 2 weeks. You don't want to assume it's constant in order to get a better measurement. The assumption is clearly false. But, errors can be calculated, and retargeting can take errors into account, because no matter what we'll always be dealing with a finite sample. Personally I don't think difficulty target variations are such a big deal, if the algorithm targets that over any long time interval, the average block time is 10 min. Bitcoin's current algorithm fails here, with increasing hashrate (as we have), it issues coins faster than its assumed schedule. -- Cheers, Bob McElrath "For every complex problem, there is a solution that is simple, neat, and wrong." -- H. L. Mencken _______________________________________________ bitcoin-dev mailing list bitcoin-dev@lists.linuxfoundation.org https://lists.linuxfoundation.org/mailman/listinfo/bitcoin-dev
