Task Scheduling in Distributed Processing Environment: A Fuzzy Approach

All practical real-time scheduling algorithms in distributed processing environment present a trade-off between their computational complexity and performance. In real-time systems, tasks have to be performed correctly and timely. Finding minimal schedule in Distributed Processing System (DPS) with constraints is shown to be NP-hard. Although some optimal algorithms have been employed in uni-processor systems, they fail when they are applied in multiprocessor systems. To alleviate these deficiencies, in this paper a fuzzy logic approach is discussed to determining the Optimal Busy Time (OBT) of the DPS considering the Execution Time (ET) and Inter Task Communication Time (ITCT) as input parameters. The complexities of the processing Time of tasks on processors and ITCT between the tasks and the imprecision of linguistic expressions are taken into consideration. In varying conditions of ET and ITCT parameters, the maximum value of OBT likely to be changes accordingly that depends on the inference engine mechanism. A detailed exposition of the application combining linguistic approach to optimize OBT considering heterogeneous environment is presented in this study.