  We study the online scheduling problem where the machines need to be
calibrated before processing any jobs. To calibrate a machine, it will take
$\lambda$ time steps as the activation time, and then the machine will remain
calibrated status for $T$ time steps. The job can only be processed by the
machine that is in calibrated status. Given a set of jobs arriving online, each
of the jobs is characterized by a release time, a processing time, and a
deadline. We assume that there is an infinite number of machines for usage. The
objective is to minimize the total number of calibrations while feasibly
scheduling all jobs.
  For the case that all jobs have unit processing times, we propose an
$\mathcal{O}(\lambda)$-competitive algorithm, which is asymptotically optimal.
When $\lambda=0$, the problem is degraded to rent minimization, where our
algorithm achieves a competitive ratio of $3e+7(\approx 15.16)$ which improves
upon the previous results for such problems.
