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Efficient coordination mechanisms for unrelated machine scheduling

We present new coordination mechanisms for scheduling selfish jobs on $m$ unrelated machines. A coordination mechanism aims to mitigate the impact of selfishness of jobs on the efficiency of schedules by defining a local scheduling policy on each machine. The scheduling policies induce a game among the jobs and each job prefers to be scheduled on a machine so that its completion time is minimum given the assignments of the other jobs. We consider the maximum completion time among all jobs as the measure of the efficiency of schedules. The approximation ratio of a coordination mechanism quantifies the efficiency of pure Nash equilibria (price of anarchy) of the induced game. Our mechanisms are deterministic, local, and preemptive. Our first coordination mechanism has approximation ratio $Θ(\log m)$ and guarantees that the induced game has pure Nash equilibria. This result improves a bound of $O(\log^2 m)$ due to Azar, Jain, and Mirrokni and uses a global ordering of the jobs according to their distinct IDs. Our second mechanism handles anonymous jobs and has approximation ratio $O(\frac{\log m}{\log \log m})$ although the game induced is not a potential game and, hence, the existence of pure Nash equilibria is not guaranteed by potential function arguments. However, it provides evidence that the known lower bounds for non-preemptive coordination mechanisms could be beaten using preemptive scheduling policies. Our third coordination mechanism also handles anonymous jobs and has a nice cost-revealing potential function. We use this potential function in order to prove the existence of equilibria and to upper-bound the price of anarchy of the induced game by $O(\log^2m)$. Our third coordination mechanism is the first that handles anonymous jobs and simultaneously guarantees that the induced game is a potential game and has bounded price of anarchy.