A proof-of-work blockchain uses a retargeting algorithm, also termed a difficulty adjustment algorithm, to manage the rate of block production in the presence of changing hashrate. To derive the parameters that guide the search for the next block, nearly all such algorithms rely on averages of past inter-block time observations, as measured by on-chain timestamps. We are motivated to seek better responsiveness to changing hashrate, while improving stability of the block production rate and retaining the progress-free property of mining. We describe a class of retargeting algorithms for which the sole inter-block time input is that of the block being searched for, and whose response is nonlinear in that time. We discuss how these algorithms allow the other consensus rules that govern allowable timestamps to be tightened, which may improve the blockchain’s effectiveness as a time-stamping machine.
Development of a Block-Based Real-Time People Counting System
