Meeting End-to-End Deadlines through Distributed Local Deadline Assignments

In a distributed real-time system, jobs are often executed on a number of processors and must be completed by their end-to-end deadlines. Without considering resource competition among different jobs on each processor, deadline requirements may be violated. The paper introduces a distributed approach to assigning local deadlines to the jobs on each processor. The approach leads to improved schedulability results by considering disparate workloads among the processors due to competing jobs having different paths. Simulation results based on randomly generated workloads indicate that the proposed approach outperforms existing work in terms of both the number of feasible task sets (between 22% and 75%) and the number of feasible jobs (between 57% and 46%).