Scheduling real time parallel structures on cluster computing with possible processor failures

Efficient task scheduling is essential for achieving high performance computing applications for distributed systems. Most of existing real-time systems consider schedulability as a main goal and ignores other effects such as machines failures. In This work we develop an algorithm to efficiently schedule parallel task graphs (fork-join structures). Our scheduling algorithm considers more than one factor at the same time. These factors are scheduability, reliability of the participating processors and achieved degree of parallelism. To achieve most of these goals, we composed an objective function that combines these different factors simultaneously. The proposed objective function is adjustable to provide the user with a way to prefer one factor to the others. The simulation results indicate that our algorithm produces schedules where the applications deadlines are met, reliability is maximized and the application parallelism is exploited.