Distributed Data Proceeding Systems Architectures Resource Efficiency Improvement on the Basis of Apriory Data about the Jobs Late Completion Times

Abstract

Purpose of research. The purpose of this study is to develop a method for improving the efficiency of distributed architectures of data processing systems operating in the fog and edge layers of the network. In conditions of high dynamics of both the network infrastructure and the load, the task of forming the architecture of data processing systems is solved regularly (migration of virtual machines, horizontal scalingб etc.) At the same time, the issue of the consumption of the residual resource of computing nodes is practically not considered, while the often used devices have relatively low capacity, and their high workload leads to a reduction in the service life. Therefore, the creation of methods for forming an architecture of a computing device system that is effective in terms of saving a computing resource is an urgent task.Methods. The main scientific methods used in this study are domain analysis, operations research methods, optimization methods and computer modeling, confirming the feasibility of the main aspects of the developed method. To improve the efficiency of placing computational tasks on the nodes of a network fragment, this paper formulated a multicriteria optimization problem, where each element of the vector objective function corresponds to an individual value of the probability of failure-free operation of a computing device. To obtain estimated values of the cost function, a priori estimates of the late completion of the solution of computational problems by nodes are used, since the resource allocated for solving depends on the allocated time, and the time for solving the problem, respectively, on the allocated computing resource. The value of the cost function is calculated on the basis of approximate a priori estimates, which leads to a positive effect in terms of the consumption of computing resources of devices.Results. The result of the study is a developed method for improving the efficiency of distributed architectures of data processing systems operating in the fog and edge layers of the network.Conclusion. The method proposed in this work allows to choose such a load distribution in order to reduce the workload of devices and thus reduce the consumption of computing resources of the devices.