  We study the problem of scheduling jobs on fault-prone machines communicating
via a shared channel, also known as multiple-access channel. We have $n$
arbitrary length jobs to be scheduled on $m$ identical machines, $f$ of which
are prone to crashes by an adversary. A machine can inform other machines when
a job is completed via the channel without collision detection. Performance is
measured by the total number of available machine steps during the whole
execution. Our goal is to study the impact of preemption (i.e., interrupting
the execution of a job and resuming later in the same or different machine) and
failures on the work performance of job processing. The novelty is the ability
to identify the features that determine the complexity (difficulty) of the
problem. We show that the problem becomes difficult when preemption is not
allowed, by showing corresponding lower and upper bounds, the latter with
algorithms reaching them. We also prove that randomization helps even more, but
only against a non-adaptive adversary; in the presence of more severe adaptive
adversary, randomization does not help in any setting. Our work has extended
from previous work that focused on settings including: scheduling on
multiple-access channel without machine failures, complete information about
failures, or incomplete information about failures (like in this work) but with
unit length jobs and, hence, without considering preemption.
