1 research outputs found

    Achieving Optimal Backlog in the Vanilla Multi-Processor Cup Game

    Full text link
    In each step of the pp-processor cup game on nn cups, a filler distributes up to pp units of water among the cups, subject only to the constraint that no cup receives more than 11 unit of water; an emptier then removes up to 11 unit of water from each of pp cups. Designing strategies for the emptier that minimize backlog (i.e., the height of the fullest cup) is important for applications in processor scheduling, buffer management in networks, quality of service guarantees, and deamortization. We prove that the greedy algorithm (i.e., the empty-from-fullest-cups algorithm) achieves backlog O(logn)O(\log n) for any p1p \ge 1. This resolves a long-standing open problem for p>1p > 1, and is asymptotically optimal as long as n2pn \ge 2p. If the filler is an oblivious adversary, then we prove that there is a randomized emptying algorithm that achieve backlog O(logp+loglogn)O(\log p + \log \log n) with probability 12polylog(n)1 - 2^{-\operatorname{polylog}(n)} for 2polylog(n)2^{\operatorname{polylog}(n)} steps. This is known to be asymptotically optimal when nn is sufficiently large relative to pp. The analysis of the randomized algorithm can also be reinterpreted as a smoothed analysis of the deterministic greedy algorithm. Previously, the only known bound on backlog for p>1p > 1, and the only known randomized guarantees for any pp (including when p=1p = 1), required the use of resource augmentation, meaning that the filler can only distribute at most p(1ϵ)p(1 - \epsilon) units of water in each step, and that the emptier is then permitted to remove 1+δ1 + \delta units of water from each of pp cups, for some ϵ,δ>0\epsilon, \delta > 0
    corecore