Maximizing reliability while scheduling real-time task-graphs on a cluster of computers

Improper scheduling of real-time applications on a cluster may lead to missing required deadlines and offset the gain of using the system and software parallelism. Most existing scheduling algorithms do not consider factors such as real-time deadlines, system reliability, processing power fragmentation, inter-task communication and degree of parallelism on performance. In this paper we introduce a new scheduling algorithm, which is based on using an objective function to guide the search for a near optimal solution. This objective function includes different criteria such as real-time deadlines, reliability, and quantitative measures of the communication, degree of parallelism and processing power fragmentation. The presence of different criteria may affect the overall acceptance rate of the applications. We also investigate the effect of reliability on the overall acceptance rate.

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