Scheduling distributed real-time tasks in the DGMF model

A,Analytical results on the real-time scheduling of multi-processor systems have focussed oil partitioning ann distributing the task set for scheduling on identical single processors,,vith the assumption that all of a task call be executed on any of a pool of identical processors. A distributed system is a set of nodes networked together Each node may have a different type of processor and performs different functions. In the distributed environment, a real-time task mag require processing on multiple nodes. However; all the nodes have to satisfy the time constraints of the task. IN this paper we show that the Liu & Layland-type classical task models must be extended to handle this type of distributed real-time tasks. We propose a Distributed Generalized Multiframe (DGMF) task model. The scheduling problem of DGMF tasks can be reduced to that of scheduling: Generalized Multiframe (CMF) tasks on a single processor We analyze the fixed priority scheduling of (D)CMF tasks and prove that the deadline-monotonic priority assignment is not optimal for the general case of frame-wise ise priority assignment. In the context of relative deadline assignment, we show that there are simple cases for which deadline-monotonic assignment is optimal.