It does not devolve into poll() scaling behaviour, even in your uniform probability scenario. To picture it, maybe it helps to consider low and high uniform pr

It does not devolve into poll() scaling behaviour, even in your uniform probability scenario. To picture it, maybe it helps to consider low and high uniform probabilities. If the uniform probability is a low enough per wait call, epoll/kqueue/etc have low cost per wait call, but so does this child-select method, because most child processes don't wake on each wait call. If the uniform probability is high enough, epoll/kqueue/etc return most of the fds, scaling just like the cost of select/poll, and child-select. So epoll/kqueue/etc and child-select match at the extremes, modulo constant factors. In general, with a constant-bounded subset size, you can say the cost of unnecessary fd polls is amortised over the necessary fd polls, because unnecessary fd polls only occur in child processes that wake due to a necessary fd poll. So the algorithmic big-O scaling of this method is still the same as epoll/kqueue/etc as the number of fds increases and the probability varies, whether it's uniform or non-uniform. No guarantees about the constant factors, though. You'd still want to tune parameters, to have enough and not too many in each subset. Constant-bounded subset size ensures scaling but not necessarily optimal performance. You can relax the constant bound and still keep the worst-case big-O scaling, if it's adaptive in the right sort of way, to better handle non-uniform probabilities with fewer processes.