The problem of scheduling tasks on $p$ processors so that no task ever gets too far behind is often described as a game with cups and water. In the $p$-processor cup game on $n$ cups, there are two players, a filler and an emptier, that take turns adding and removing water from a set of $n$ cups. In each turn, the filler adds $p$ units of water to the cups, placing at most $1$ unit of water in each cup, and then the emptier selects $p$ cups to remove up to $1$ unit of water from. The emptier's goal is to minimize the backlog, which is the height of the fullest cup. The $p$-processor cup game has been studied in many different settings, dating back to the late 1960's. All of the past work shares one common assumption: that $p$ is fixed. This paper initiates the study of what happens when the number of available processors $p$ varies over time, resulting in what we call the \emph{variable-processor cup game}. Remarkably, the optimal bounds for the variable-processor cup game differ dramatically from its classical counterpart. Whereas the $p$-processor cup has optimal backlog $\Theta(\log n)$, the variable-processor game has optimal backlog $\Theta(n)$. Moreover, there is an efficient filling strategy that yields backlog $\Omega(n^{1 - \epsilon})$ in quasi-polynomial time against any deterministic emptying strategy. We additionally show that straightforward uses of randomization cannot be used to help the emptier. In particular, for any positive constant $\Delta$, and any $\Delta$-greedy-like randomized emptying algorithm $\mathcal{A}$, there is a filling strategy that achieves backlog $\Omega(n^{1 - \epsilon})$ against $\mathcal{A}$ in quasi-polynomial time.

Thanks. We have received your report. If we find this content to be in
violation of our guidelines,
we will remove it.

Ok