Fault-Tolerant Partitioning Scheduling Algorithms in Real-Time Multiprocessor Systems

Abstract

This paper presents the performance analysis of several well-known partitioning scheduling algorithms in real-time and fault-tolerant multiprocessor systems. Both static and dynamic scheduling algorithms are analyzed. Partitioning scheduling algorithms, which are studied, are heuristic algorithms that are formed by combining any of the bin-packing algorithms with any of the schedulability conditions for the rate-monotonic (RM) and earliest-deadline-first (EDF) policies. A tool is developed which enables to experimentally evaluate the performance of the algorithms from the graph of tasks. The results show that among several partitioning algorithms evaluated, the RM-small-task (RMST) algorithm is the best static algorithm and the EDF-best-fit (EDF-BF) is the best dynamic algorithm, for non fault-tolerant systems. For fault-tolerant systems which require about 49% more processors, the results show that the RM-first-fit decreasing utilization (RM-FFDU) is the best static algorithm and the EDF-BF is the best dynamic algorithm. To decrease the number of processors in fault-tolerant systems, the RMST is modified. The results show that the modified RMST decreases the number of required processors between 7% and 78% in comparison with the original RMST, the RM-FFDU and other well-known static partitioning scheduling algorithms