Cloud computing simulation model with a sporadic mechanism of parallel task solving control

A simulation model of a computer system built in the Simulink (SimEvent) environment is considered. According to the queuing theory, the system is classified as G/G/n/∞. This means that there are multiple input streams in the system, their queue is infinite, and two feedbacks are applied. These feedbacks reflect the situation of the repeated processing in case of failure or lack of a solution at the first processing attempt. The system architecture under consideration is focused on parallel processing of a certain class of tasks, while the tasks themselves are data-independent. The model is investigated for uniformly distributed and exponential input streams. The situation of continuous streams for several types of tasks is considered, for which priorities and the numbers of partitioning fragments vary. The number of fragments determines the degree of parallelism in the execution of the task. The paper shows a method for automatically determining the optimal number of task fragments to guarantee its completion within the target period. The use of sporadic control mechanisms for a number of the task fragments received in a continuous stream and the priorities managing of each of the task fragments are proposed. The proposed mechanism of the sporadic management made it possible to significantly speed up the tasks completion within the target deadline. As a result, the load on the computing system has been reduced and the efficiency of its operation has been increased. The use of the proposed algorithms significantly simplifies the scheduling mechanisms in the computer system, which allows you to exclude the scheduler