St. Petersburg State University of Telecommunications

About: St. Petersburg State University of Telecommunications is a education organization based out in Saint Petersburg, Russia. It is known for research contribution in the topics: Computer science & The Internet. The organization has 408 authors who have published 465 publications receiving 2160 citations.

Behavioral Analysis of Resource Allocation Systems in Cloud Infrastructure

Abstract: This paper presents behavioral analysis of resource allocation systems in cloud infrastructure. This analysis is performed on the basis of these systems monitoring and machine learning. To do it, the system creates a model of normal system behavior using learning set. The constructed model is used as a reference. Recognition of an abnormal behavior of the system is based on the comparing of the normal behavior with the current one. The results represent the beginning of the research. In the continuation, the issues of anomaly detection based on virtual machine (instance) resource utilization metrics will be analyzed. Also, an algorithm for determining anomalies will be developed based on a comprehensive analysis of the CPU, RAM, HDD resources usage. For enhancing of the anomalies detection accuracy it is planned to increase the period of learning.

Analysis of the Packet Path Lengths in the Swarms for Flying Ubiquitous Sensor Networks

Abstract: The article gives an approach for estimating the packet path length between the nodes for Flying Ubiquitous Sensor Networks. Authors show that such networks may be represented as three-dimensional swarms of nodes. The mathematical models for the ball and cubic swarms are given, as well as the simulation approach for the other shapes. Also two types of network architecture are considered – direct transfer and multi-hop.

Information environment for the training of highly qualified personnel in the system of continuous education

Abstract: The results of the development of an information environment for training specialists at all stages of training are presented. The environment is based on three principles: agency, information self-service and managed information openness. The issues of training specialists for specific vacancies are considered, including the organization of the educational process of students on individual curricula coordinated with enterprises, which ensures guaranteed employment and replenishment of the staff deficit of enterprises, as well as providing the most convenient for the student training regime, including the use of electronic and remote education, on individual trajectories of training.

The Role of the Unified Educational Cyber Environment in Improving the Quality of Training of Engineer Personnel

Abstract: A concept for formation of a single cyber environment of higher education has been represented. The principles of building such environment have been reviewed and its effects on the functioning of higher educational establishments and improved quality of staff training have been analyzed. A model of the basic educational program which is the basis for constant information support of training highly qualified specialists for science-intensive industries has been proposed. This model will ensure minimization of routines, ensure coordinated self-documented learning process within which all reporting documentation is formed automatically on information contained in the educational program model. The results of developing an e-learning system based on interactive teaching materials, integrated in cyber environment of virtual enterprises have been represented.

Models of QOE ensuring for OTT services

Abstract: This article discusses the main models that contribute to improving the quality of OTT services. The main parameter for quality assessment was chosenQoE-Quality of Experience. An analysis was made of a number of factors that directly affect the assessment of QoE. The second part of the article deals with models that can provide the necessary level of quality for OTT services. These models were divided into three groups: traffic-based models, application-based models, and speed-based models. The main task of the study is to find optimal solutions to ensure the quality of OTT services.