1 research outputs found
Truthful Online Scheduling with Commitments
We study online mechanisms for preemptive scheduling with deadlines, with the
goal of maximizing the total value of completed jobs. This problem is
fundamental to deadline-aware cloud scheduling, but there are strong lower
bounds even for the algorithmic problem without incentive constraints. However,
these lower bounds can be circumvented under the natural assumption of deadline
slackness, i.e., that there is a guaranteed lower bound on the ratio
between a job's size and the time window in which it can be executed.
In this paper, we construct a truthful scheduling mechanism with a constant
competitive ratio, given slackness . Furthermore, we show that if is
large enough then we can construct a mechanism that also satisfies a commitment
property: it can be determined whether or not a job will finish, and the
requisite payment if so, well in advance of each job's deadline. This is
notable because, in practice, users with strict deadlines may find it
unacceptable to discover only very close to their deadline that their job has
been rejected