UDK 004.942 Doi: 10.31772/2587-6066-2020-21-4-492-498
MODELS AND METHODS OF OPTIMAL CONTROL OF SOFTWARE AND TECHNICAL CONFIGURATION OF HETEROGENEOUS DISTRIBUTED INFORMATION PROCESSING SYSTEMS
G. A. Ontuzheva
Siberian Federal University; 79, Svobodny Av., Krasnoyarsk, 660041, Russian Federation
The article discusses formalization of the problem of heterogeneous distributed information processing systems (HDIPS) software and hardware configuration management. A formal description of possible optimality criteria for the HDIPS software and hardware configuration is given. The HDIPS model in terms of queuing theory is proposed. The problem of allocating the HDIPS computational resources is formulated as a transport problem according to time criterion with atomic needs. The algorithm for solving this problem is proposed and the boundaries of its applicability to the HDIPS are determined. To meet the selected optimality criterion, the analysis of the HDIPS software and hardware configuration applying its formal model, using the queuing theory methods is presented. HDIPS is presented as a queuing network, where each computing node and route control unit is a mass service system. The problem of computing resource allocation in HDIPS is presented as a transport problem according to the time criterion with atomic needs. The least time algorithm for indivisible needs takes into account the indivisibility condition.
Keywords: distributed information processing systems, transport problem, queuing systems, software and hardware configuration, management of software and hardware resources, management optimization.
References

1. Antamoshkin O. A., Kilochitskaya T. R., Ontuzheva
G. A., Stupina A. A., Tynchenko V. S. Multicriterion
problem of allocation of resources in the heterogeneous
distributed information processing systems. Journal
of Physics: Conference Series. 2018, Vol. 1015, P. 32162.
Doi: 10.1088/1742-6596/1015/3/032162.
2. Antamoshkin O. A. [Multi-agent automation system
for monitoring, forecasting and control in emergency
situations]. Mezhdunarodna nauchna shkola “Paradigma”
[Paradigma International Scientific School].
Varna, 2015, P. 18–28 (In Russ.).
3. Glazunov V. V., Kurochkin M. A., Popov S. G.
[Method for evaluating message transmission routes in
telematic networks of vehicles based on the logicalprobabilistic
method]. Intellektual'nye tekhnologii na
transporte, 2015. Vol 1 (In Russ.). Available at:
https://cyberleninka.ru/article/n/metod-otsenki-marshrutov-
peredachi-soobscheniy-v-telematicheskih-setyahtranspotrnyh-
sredstv-na-osnove-logiko-veroyatnostnogometoda
(accessed: 25.10.2020).
4. Bigham J., Du L. Cooperative negotiation in a
multi-agent system for real-time load balancing of a mobile
cellular network ACM, 2003. P 568–575. Doi:
10.1145/860575.860666.
5. Kantamneni A., Brown L. E., Parker G., Weaver
W. W. Survey of multi-agent systems for microgrid
control. Engineering applications of artificial intelligence.
2015, Vol. 45, P. 192–203. Doi:
10.1016/j.engappai.2015.07.005.
6. Khritankov A. S. [Modeli i algoritmy raspredeleniya
nagruzki]. Informatsionnye tekhnologii i vychislitel'nye
sistemy. 2009, Vol. 2, P. 65–80 (In Russ.).
7. Skobelev P. O. [Intelligent resource management
systems in real time: development principles, experience
of industrial implementations and development prospects].
Prilozhenie k teoreticheskomu i prikladnomu
nauchno-tekhnicheskomu zhurnalu “Informatsionnye
tekhnologii”. 2013, No. 1, P. 1–32 (In Russ.).
8. Dmitriev V. N., Sorokin A. A., Kuok Ch. T. [Improving
the efficiency of traffic management in heterogeneous
data transmission systems under conditions of uncertainty].
Vestnik Astrakhanskogo gosudarstvennogo
tekhnicheskogo universiteta. Seriya: Upravlenie, vychislitel'naya
tekhnika i informatika. 2015, No. 3, P. 66–77
(In Russ.).
9. Krutolapov A. S. [Ensuring the quality of service in
information exchange networks]. Vestnik
Voronezhskogo instituta GPS MChS Rossii. 2013, No. 1,
P. 18–22 (In Russ.).
10. Kammoun H. M., Kallel I., Casillas J., Abraham
A., Alimi A. M. Adapt-Traf: An adaptive multiagent road
traffic management system based on hybrid anthierarchical
fuzzy model. Transportation Research Part
C: Emerging Technologies. 2014, No. 42, P. 147–167.
Doi.org: 10.1016/j.trc.2014.03.003.
11.GOST 15971–90. Sistemy obrabotki informatsii.
Terminy i opredeleniya [State Standard 15971–90. Information
processing systems. Terms and Definitions]. Moscow,
Standartinform Publ., 1991, 12 p.
12. Ontuzheva G. A. [Methods for optimizing the distribution
of resources of a geographically distributed
multi-level computer network]. Mezhdunarodna nauchna
shkola "Paradigma" [Paradigma International Scientific
School]. Varna, 2015, P. 185–190 (In Russ.).
13. Zhozhikashvili V. A., Vishnevskiy V. M. [Queuing
networks: Theory and application to computer networks].
Seti massovogo obsluzhivaniya: Teoriya i primenenie
k setyam EVM. Moscow, Radio i svyaz' Publ., 1988,
191 p.
14. Hammer P. L. Timeminimizing transportation
problems. Naval Research Logistics Quarterly. 1969,
No. 3 (16), P. 345–357. Doi:10.1002/nav.3800160307.
15.Ontuzheva G. A., Bruchanova E. R., Rudov I. N.,
Pikov N. O., Antamoshkin O. A. Simulation modelling
of the heterogeneous distributed information processing
systems. In IOP Conference Series: Materials Science
and Engineering. 2018, Vol. 450, No. 5, P. 05. Doi:
10.1088/1757-899X/450/5/052018.


Ontuzheva Galina Aleksandrovna – Assistant of the Department of Information Technologies in Creative and
Cultural Industries; Siberian Federal University. E-mail: gontuzheva@sfu-kras.ru.


  MODELS AND METHODS OF OPTIMAL CONTROL OF SOFTWARE AND TECHNICAL CONFIGURATION OF HETEROGENEOUS DISTRIBUTED INFORMATION PROCESSING SYSTEMS