NEW METHODOLOGICAL APPROACHES TO WORK WITH STUDENTS IN THE CONDITIONS OF DIGITALIZATION

The problem of finding new approaches to the organization of training has become particularly important in times of digital turbulence. Today, during the coronovirus pandemic, there is a transition from the established traditional technologies of organizing training to the widespread use of digital technologies in the online learning system, which has covered the whole world. The purpose of the research is to substantiate, develop and test the model of the electronic coworking environment in the system of higher pedagogical education. At the same time, the coworking environment is considered as an educational virtual cluster. Such a basic platform is an educational content that includes all educational products. To solve the tasks, we used research methods: design and modeling; studying the products of the coworking environment, conversations in chats, questionnaires; mathematical processing methods. The presented research results revealed the advantages of the coworking environment: successful socialization, minimization of time and economic resources, expansion of business partnerships, mutual assistance and a comfortable atmosphere. The analysis of studies on the criterion of coworking productivity revealed an increase in the mobility of students, an increase in the satisfaction index and the effectiveness of communication. Testing the e-coworking model proves its advantages and prospects for implementation in the system of higher pedagogical education. The conducted research allowed us to come to the following conclusion: the introduction of remote technology models in the training of students and undergraduates based on the Moodle system in the form of a coworking environment is a powerful innovative resource. We predict the expansion of the industry of coworking spaces and see the need to continue scientific developments in this direction.

Experience of OpenStack Test Deployment and Comparison of Virtual and Real Cluster Environments

Introduction. A brief overview of the properties and architecture of one of the components of the National Cloud of Open Science prototype – the cloud platform OpenStack is given. The list of software and hardware components of the OpenStack test cloud environment and the sequence of actions required for the deployment of both OpenStack itself and the Slurm virtual cluster environment for portable, scalable, reproducible scientific biomedical computing are presented. The purpose of the paper is a description of the experience of test deployment of OpenStack to create a scalable computing environment for reproducible scientific computing using modern technological solutions, which can be applied to both cloud (OpenStack, AWS, Google) and cluster platforms (Slurm). Results. The structure of the created test containerized (using Singularity technology) biomedical application, which contains modern software and libraries and can be used in conventional and cloud virtual cluster environments is briefly described. The results of a comparative test of this application in the virtual cluster environment Slurm under the control of OpenStack and in the node of cluster SKIT-4.5 in the V.M. Glushkov Institute of Cybernetics of the NAS of Ukraine are given. Information on solving the problem of finding the optimal in terms of saving resources scaling parameters for the developed application in two comparable cluster environments is given. Some features of the use of these cluster environments are clarified, in particular, a comparison of the dependence of the application speed on the number of parallel processes for two cluster environments is presented. Empirical data are presented in graphical form, which illustrate the nature of the load on the OpenStack server and the use of RAM on the number of parallel processes. Possibilities of portability between the specified cluster environments, scaling of calculations and maintenance of reproducibility of calculations for the offered test application are demonstrated. The advantages of using OpenStack technology for scientific biomedical calculations are pointed out. Conclusions. The described example of test deployment and use of OpenStack gives an idea of the requirements for the necessary technical base to ensure the reproducibility of scientific biomedical calculations in cloud and cluster environments. Keywords: cloud technologies, reproducible calculations, cluster platform.

Modeling Red Blood Cell Viscosity Contrast Using Inner Soft Particle Suspension

The inner viscosity of a biological red blood cell is about five times larger than the viscosity of the blood plasma. In this work, we use dissipative particles to enable the proper viscosity contrast in a mesh-based red blood cell model. Each soft particle represents a coarse-grained virtual cluster of hemoglobin proteins contained in the cytosol of the red blood cell. The particle interactions are governed by conservative and dissipative forces. The conservative forces have purely repulsive character, whereas the dissipative forces depend on the relative velocity between the particles. We design two computational experiments that mimic the classical viscometers. With these experiments we study the effects of particle suspension parameters on the inner cell viscosity and provide parameter sets that result in the correct viscosity contrast. The results are validated with both static and dynamic biological experiment, showing an improvement in the accuracy of the original model without major increase in computational complexity.

Availability-Aware Multi-Objective Cluster Allocation Optimization in Energy-Efficient Datacenters

With increasing network virtualization, data centre's workloads are modified in depth to serve various service-oriented applications, often defined by a time-bound service response, which, in turn, places a heavy demand on data center networks. Network virtualization in computing is the technique of integrating network resources and network functions in hardware and software into one virtual network, the software-based administration entity. Number of people ask for the server simultaneously, thereby slowing down the service.It is so costly to buy a new server that we developed a virtual system by creating a virtual system. With a trend to increase the number of cloud apps in the datacenter. There are numerous physical machines (PMs) linked via switches in the datacenter. Hardware PM resources for adaptable and elastic computing capabilities are usually shared via virtualization technology. Usually a cloud application is implemented in a virtual cluster that includes many virtual machines which occupy PM resources on request.