autonomous distributed system

The problem of organizing data collection processes in autonomous distributed systems has been considered, in particular, in autonomous mobile cyber-physical systems and autonomous distributed environmental monitoring systems. A model of decentralized control of adaptive data collection processes based on the principle of equilibrium has been proposed. Using this model, the problem of coordinating joint collective actions of adaptive data collection processes is studied from the point of view of finding an effective scheme for their complementarity in the absence of a control center.

A method of structural adaptation of data collection processes has been developed based on reinforcement learning of the decision block on the choice of actions at the structural and functional level subordinated to it, which provides a more efficient distribution of measuring and computing resources, higher reliability and survivability of information collection subsystems of an autonomous distributed system compared to methods of parametric adaptation.