Vladimir Rykov
Doctor of Physico-Mathematical Sciences

Stay on the edge of modern scientific achievements and "keep in rein the research authorities."

Scientific interests:

Graduate of the faculty of physical and mathematical sciences of Lomonosov Moscow State University. Specialty - "Mathematics".


Defended his Ph.D. thesis: "Controllable Queuing systems" (Ph.D. in Engineering Sciences), Central Economics and Mathematics Institute, USSR Academy of Sciences.


Associate Professor at the Department of Applied Mathematics and Computer Simulation at the Gubkin Russian State University of Oil and Gas.


Researcher and guest lecturer at the Department of Stochastics at the TU Bergakademie, Germany.


Defended his doctoral thesis: «Semi-regenerating stochastic processes and their application in queuing theory», Lomonosov Moscow State University.

1993 – present

Professor of the Department of Applied Mathematics and Computer Simulation, Gubkin Russian State University of Oil and Gas.


Guest lecturer at the Engineering Science Department, Technion, Haifa, Israel.


Guest lecturer at the Engineering and Economic Science Department, Vrai University, Amsterdam, Netherlands.


Guest professor at the Mathematical Statistics Department of the Mathematics and Science Faculty of the Kettering University, Flint, USA.

2014 – present

Professor at the Applied Probability and Informatics Department of the RUDN University.

Lectures on the following courses:

  • Probability theory and mathematical statistics
  • Stochastic processes
  • Computer simulation
  • Reliability of technical systems and technological processes
  • Stochastic networks


  • Stochastic networks and systems
  • Queueing theory
  • Reliability theory
  • Head of research grants of the RFPF

Scientific interests

  • Managed queueing systems
  • Stability and sensitivity of stochastic systems
  • Statistics of accelerated trials
In this paper, we study the accuracy of different estimators of the effective bandwidth (EB), i.e. a required server capacity C to guarantee a given QoS requirement. We assume that the input sequence is regenerative and study the accuracy of the estimator which is based on the actual regeneration cycles of the basic process describing dynamics of the server. Then, by simulation, we compare this estimator with alternative estimators. In particular, we compare the property of the regeneration-based estimation and the estimation obtained by the so-called Batch Means method. It is shown that the regeneration-based estimator of C in all cases overestimates predefined QoS requirement. Then we discuss how this property can be applied to calculate the required EB for the components of highly reliable telecommunication systems.
This book is based on a lecture course to students specializing in the safety of technological processes and production. The author focuses on three main problems in technological risks and safety: elements of reliability theory, the basic notions, models and methods of general risk theory and some aspects of insurance in the context of risk management. Although the material in this book is aimed at those working towards a bachelor's degree in engineering, it may also be of interest to postgraduate students and specialists dealing with problems related to reliability and risks.
As it known the optimal policy which minimizes the long-run average cost per unit of time in a multi-server queueing system with heterogeneous servers without preemption has a threshold structure. It means that the slower server must be activated whenever all faster servers are busy and the number of customers in the queue exceeds some specified for this server threshold level. The optimal thresholds can be evaluated using the Howard iteration algorithm or by minimizing the function of the average cost which can be obtained in closed form as a function of unknown threshold levels. The both cases have sufficient restrictions on dimensionality of the model. In present paper we provide a heuristic method to derive expressions for the optimal threshold levels in explicit form as functions of system parameters like service intensities, usage and holding costs for an arbitrary number of servers. The proposed method is based on the fitting of the boundary planes between the areas where the optimal threshold takes a certain value.