Abstract
The cloud computing (CC) infrastructure is considered as an adaptation object and the process of adaptation of cloud computing as an optimization one. The general statement of the task on adapting the disciplines of providing computing resources to users of the IA has been performed. It is proposed to use dynamic adaptive mixed (with absolute and relative priorities) discipline of providing services with computing resources to users, in which dynamic adaptation to the changing conditions and conditions of the CC system and the environment set by consumers of computing resources is possible. The direction of the solution of the problem of optimization of dynamic adaptive mixed discipline is given. A well-known optimization functional is proposed, which is based on the assumption that the results of using the computing resources by the user (solving user tasks) depreciate in proportion to the time spent in the decision queue and the solution in the CC system. Other functionals are also possible with time cons-traints. This is relevant for modern global real-time information and analytical systems using cloud computing technologies and can be critical for limited computational resources of CC. For example, the goal of adaptation can be to meet the constraints on the efficiency index, given in the form of equations or inequalities. In any case, this formulation of the adaptation task necessitates the implementation in the IA of several or one mixed discipline of providing services with computing resources to users. It is indicated that the optimization problem is solved by an iterative method using the appropriate analytical models for the functioning of the CC.
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