Distributed system of virtual machines for self-organized networks
Introduction: Active data, being fragments of executable code transmitted between the nodes of an active network, are an effective mechanism for the operation of software-reconfigurable distributed systems. Previously, in the works devoted to active data, not enough attention was paid to the implementation of the runtime environment (the processor) for the executable code of active data, as well as to the issues of building hypervisors and load balancing in distributed systems. Purpose: Developing principles for the construction of virtual machines with active data, providing the reconfigurability of the target devices and network flexibility in general. Evaluating the possibility of using the existing approaches to load balancing for networks with active data. Methods: Our study uses the principles of software-defined system development, the conception of active data, theoretical foundations and technology of virtualization. Results: Is has been proposed to use a distributed system of virtual machines as an active data execution environment, based on the object-oriented approach to creating distributed applications. Each node of such a distributed system of virtual machines can act as either a control or slave node during the object interaction. Based on the developed approach, we proposed to solve the problem of building a network of repeaters using active data, considering an unmanned aerial vehicle as an element of an active info-communication network which supports the active data technology. Since a distributed system of virtual machines enables asymmetric distribution of decentralized network nodes, a method has been developed for a distributed system whose nodes are unmanned aerial vehicles and a control node, to control the asymmetry value by creating objects of various decomposition levels. Practical relevance: The proposed methods provide a way to control the resource consumption of the nodes of a distributed software-reconfigurable network and the amount of network data transmitted. For dynamic management of the load on the network nodes, a resource manager architecture and a resource allocation algorithm are developed.