Provably Good Scheduling of Sporadic Tasks with Resource Sharing on a Two-Type Heterogeneous Multiprocessor Platform

Consider the problem of scheduling a set of implicit-deadline sporadic tasks to meet all deadlines on a two-type heterogeneous multiprocessor platform where a task may request at most one of IR1 shared resources. There are 77-ci processors of type-1 and 7n2 processors of type-2. Tasks may migrate only when requesting or releasing resources. We present a new algorithm, FF-3C-vpr, which offers a guarantee that if a task set is schedulable to meet deadlines by an optimal task assignment scheme that only allows tasks to migrate when requesting or releasing a resource, then FF-3C-vpr also meets deadlines if given processors 2+3 [vertical bar R vertical bar/min(m(1),m(2)) times as fast. As far as we know, it is the first result for ml resource sharing on heterogeneous platforms with provable performance.