A TECHNIQUE OF EFFICIENT COMPUTING IN DISTRIBUTED HETEROGENEOUS DYNAMIC ENVIRONMENTS

Currently, the relevance of implementing distributed computing in geographically distributed heterogeneous dynamic computing environments has increased. This is due to both the need to localize computing outside of cloud structures, on the one hand, and the development of computing and network technologies, on the other. The limited computing resources of devices and their autonomy raise the issue of optimizing computing processes implemented in a distributed manner. Studying the issue of increasing the efficiency of organizing computing by distributing computing resources, it was concluded that the currently used models of environments and formulations of problems for optimizing the use of computing resources do not take into account the resource costs that appear both during data transit over the network and in the case of data transfer between computing tasks, and do not take into account the overhead costs that appear when solving the resource distribution problem. This article proposes a general formulation of the multicriterial optimization problem, where the controlled parameters include the expenditure of computing resources on data transfer through transit devices and the computational complexity of solving the problem of distributing computing resources. The developed method of organizing efficient computations in distributed heterogeneous dynamic environments implements a greedy strategy for selecting metaheuristic optimization algorithms that allow achieving a given accuracy with minimal resource costs with the possibility of improving the obtained result within the constraints of the computational resource allocation problem. The novelty of the research results lies in a new formulation of the resource allocation problem and the method for solving it. The results of the experimental study confirm the effectiveness of the developed method, allowing to reduce the computational complexity of solving the problem by 2 times, taking into account the specified requirements for the accuracy of the obtained solution.