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Title
Research areas
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general
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27005c521b2840a68b1137b69a0bbe8c
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https://asvk.cs.msu.ru/en/scientific-activity/research-areas/
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https://asvk.cs.msu.ru/en/
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2026-03-17T08:18:51+00:00
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Research areas

Source: https://asvk.cs.msu.ru/en/scientific-activity/research-areas/ Parent: https://asvk.cs.msu.ru/en/

Research areas

Research areas

Department labs

Publications

Reports

Conferences

Machine learning methods in embedded systems

Within this direction, the following methods are being developed:

Network Processor Architecture

Research directions in this area are as follows:

SDN Security

Research directions in this area are as follows:

Distributed Controlplane in SDN

Research directions in this area are as follows:

Additional Functionality at the Data Transmission Level for Programmable Network Devices (Programmable Dataplane)

Modern switching equipment provides opportunities for programming additional logic for packet processing. This allows a switch to perform some tasks without the controller’s involvement, thereby ensuring a higher degree of responsiveness to changes in the network.

Within this direction, the following works are being carried out:

Development of Network Applications for the SDN Controller (SDN Applications)

SDN offers extensive opportunities for creating innovative applications that implement previously inaccessible logic in traditional networks.

Within this direction, the following works are being carried out for the RUNOS 2.0 controller:

Development of New Programming Languages for SDN (SDN Programming)

Within this direction, the following works are being carried out:

Intelligent Network Interaction Systems in Heterogeneous Networks

Today, the Internet of Things (IoT) consists of loosely connected disjointed networks. For example, modern cars operate several networks at once: one manages engine operation, another — safety systems, a third supports communication, etc. In office and residential buildings, many networks are also installed for heating, ventilation, air conditioning, telephone communication, security, lighting management. As the IoT evolves, these and many other networks will be connected to each other and gain broader capabilities in security, analytics, and management.

Network Modeling and Prototyping Systems

When researching various properties of computer networks, simulation modeling tools are often used. The necessary detail of the simulation model of a computer network depends on the goals of modeling and is determined by the researcher when preparing the simulation experiment. The detail and accuracy of the simulation model depend on the choice of the level of abstraction of the object of modeling, as well as the choice of the mathematical apparatus in terms of which the model is constructed.

The laboratory is developing an approach to building simulation models based on lightweight virtualization technology, which allows for effective scaling of the computer network model, as well as reducing labor costs for its calibration and identification.

Technologies for Organizing and Managing Computations in a Cloud Environment

Network Functions Virtualization (NFV) is a concept of separating network functionality and the equipment that implements it through virtualization technology of physical resources.

NFV technology allows, through the virtualization of physical resources (computational, network, and storage data), to programmatically implement the necessary functionality on standard equipment. Thus, the logic of the service is made independent of the hardware on which it is executed. The engineering of “virtual network function” (VNF) depends on the goals for which the network function virtualization infrastructure is built, who builds this infrastructure, and for what purposes.

Examples of network functions virtualization include services for analyzing, managing, and engineering network traffic. For example, for telecom operators, a virtual network function is an entity that implements the functionality of specialized software and hardware network devices (so-called appliances) for switching, routing, filtering, balancing, and processing traffic. Other examples include IP telephony, video conferencing, EPC, billing, DPI (Deep Packet Inspection), traffic engineering, and monitoring, etc.

Real-Time Information and Control Systems

Real-time information and control systems (RTIC) have the following specifics:

Data Center Resource Allocation Algorithms

The efficiency of cloud platforms and the use of physical resources of data centers largely depends on the algorithm for mapping requests to physical resources of the data center. The proposed approaches to improving the efficiency of using physical resources of the data center are based on expanding the functionality and increasing the accuracy of the algorithm for mapping requests to physical resources, used in the cloud platform scheduler. Various classes of algorithms are considered for mapping virtual resources to physical resources of the data center.

Adaptive Communication

One of the most relevant research directions in the field of computer networks is the development of intelligent network management methods that would improve its performance by more rational use of available resources and optimization of network operation for specific application tasks. Such optimizations often have a fundamental importance, as they can create a competitive advantage, for example, in organizing cloud computing, streaming broadcasting using content delivery networks, building interactive online services and games, consolidating sensors and actuators that form the basis of the Internet of Things technology.

Research areas

Department labs

Publications

Reports

Conferences