Minimizing The Effect Of Processing Power Fragmentation While Scheduling Real-Time Task-Graphs On A Cluster Of Computers

Scheduling a large number of applications on a cluster-computing environment is a serious obstacle to achieving good performance. This becomes more critical in realtime systems. Much of the current allocation and scheduling work dealing with real-time applications has not provided mechanisms to satisfy the application performance requirements while maximizing processing power utilization. In this paper we introduce a new scheduling algorithm, which is based on using an objective function to guide the search for a feasible solution. This objective function includes different criteria to achieve: 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. In this paper we investigate the effect of the processing power fragmentation on the overall acceptance rate.