Distributed computing technologies development has allowed uniting geographically distributed resources and has provided an opportunity for effective resource intensive problemsolving in various fields of science and technology. At the same time a set of problems, which demands the development of new approaches, taking into account contemporary Internet technologies implementation, has risen. In this paper a problem of workload relocation in distributed computer- aided design system (DCAD) operating in the “fog” environment was considered. The goal of this paper is ontological approach development to workload relocation problem-solving in DCAD taking into account some “fog” environment features. The ontological approach involves an ontological procedure implementation, which allows “filtering” the candidate-nodes, which have insufficient resources for workload relocation. The scientific novelty of this paper is ontological models using for workload relocation problem-solving in DCAD. It allows reducing the number of candidate-nodes in the “fog” for workload relocation, thereby contributing to reduce the time of location process modeling and, consequently, the total time of workload relocation problem- solving is also reduced. The fundamental difference of presented approach is domain knowledge, represented in ontological model, applying for workload relocation problem-solving. The experimental study results have shown the expediency of ontological analysis for workload relocation problem-solving .
The paper considers the problem of workload distribution in a group of unmanned aerial vehicles (UAVs) when monitoring a certain area in a changing environment, which has a direct impact on the onboard energy resources consumption. The stage of a monitoring problem-solving, which includes the distribution of UAVs over scanning bands, is described here. When this stage is carried, there is no opportunity to take into account the factors of environmental impact. But these factors are crucial due to the limited onboard energy resources. In this regard, a situation is very likely when the UAV is not able to complete the sub-task assigned to it, which jeopardizes the completion of the entire mission of the group. To avoid this situation, it is proposed to use the technique of a decision-making on the need to relocate the workload in a group of mobile robots (MR). The decision-making is based on the ontological analysis procedure, which allows limiting the number of choices for workload relocation. The ontology model of the workload distribution in a group of UAVs was developed. This model takes into account the possibility of additional performance involvement either by means of the resources of neighboring UAVs, or by means of devices of the "foggy" layer. Examples of production rules are given, on the basis of which a decision is made on the need to relocate the workload. A comparative estimation of the resources volume involved in the implementation of two methods of workload relocation problem solving, depending on the frequency of changes in environmental conditions, is carried out. The results of computational experiments have shown that the method based on ontological analysis is more efficient in comparison with the method based on LDG (Local Device Group) in terms of the amount of resources involved. This makes it possible to increase the time of joint mission implementation by the UAV group.
