THE MODIFIED INFORMATION TECHNOLOGY FOR THE DISTRIBUTION OF RESOURCE TASKS FOR CLOUD COMPUTING SYSTEMS
AbstractThe object of the research is the process of distribution a pool of input tasks for computing resources in hybrid cluster systems. The subject of the research is information technology of distribution tasks for computing resources of hybrid cluster systems. The goal is to develop and to implement a simulation stage in a modified information technology for distributing the incoming task pool to the computing power of hybrid cluster systems. Tasks: to modify the existing information technology of task distribution on the basis of mathematical models of tasks, computing resources and distribution methods; to develop an information system that will perform an automated process of collecting and processing the data; to form a series of experiments on the distribution of the input task pool, based on the distribution methods implemented in the simulation environment. Research methods are based on the use of the theory of sets, the general theory of systems and the theory of simulation modeling. The results received. The modified information technology of distribution of program tasks of big dimension for computing resources for the systems of cloud computing with the use of the simulation environment of modeling with the subsequent choice of the best dispersion plan on each pool of input tasks is offered. The proposed information technology has been introduced into a simulation environment that allows reproducing the process of functioning of elementary events occurring in the real hybrid cluster systems while preserving the logic of their interaction in a real time. Conclusions: The proposed information technology combines the processes of collecting, storing, processing and transmitting data using the offered distribution methods, means for further analyzing the results of modeling and deciding whether to perform a specific action (choosing the best distribution plan). The use of a set of distribution methods in the simulation environment allows to conduct a series of experiments and, based on the results obtained, select the best distribution plan for a particular input task pool (on the basis of the selected strategy of distribution).
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