Abstract
In the work a multichannel queueing network with a general input flow is considered [3]. There are no restrictions on the structure of the input flow. Heavy traffic conditions on the network parameters are introduced. A functional limit theorem for the service process of the network is proved provided that the conditions are satisfied. Approximative Gaussian process is constructed. An additional splittability condition for the switching matrix of the network yields an opportunity to merge network nodes and to reduce dimension of the limit process at the Gaussian approximation scheme. Convergence is proved in the uniform topology, which enables solving optimization problems for correspondent functionals.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Gnedenko, B.V., Kovalenko, I.N.: Introduction to Queueing Theory. Springer, Birkhauser, Boston Inc. (1989)
Théorie des files d’attente 1, 2. In: Anisimov, V. Limnios, N. (eds.) Tendances avancées. ISTE Editions Ltd. (2021)
Massey, W.A., Witt, W.: A stochastic model to capture space and time dynamics in wireless communication systems. Probab. Eng. Inf. Sci. 8, 541–569 (1994)
Moiseev, A., Nazarov, A.: Tandem of infinite-server queues with Markovian arrival process. In: Vishnevsky, V., Kozyrev, D. (eds.) DCCN 2015. CCIS, vol. 601, pp. 323–333. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-30843-2_34
Gusak, D.V., Korolyuk, V.S.: Asymptotic behavior of semi-\(\rm M\)arkov processes with a splittable state set. Probab. Theory Math. Stat. 5, 43–50 (1971). (in Russian)
Korolyuk, V., Turbin, A.: Mathematical Foundation of the State Lumping of Large Systems. Springer, Dordrecht (1993)
Anisimov, V.V.: Asymptotic enlargement of the states of random processes. Cybernetics 9, 494–504 (1973). https://doi.org/10.1007/BF01069207
Korolyuk, V.S., Limnios, N.: Stochastic Systems in Merging Phase Space. World Scientific, Singapore (2005)
Anisimov, V.V.: Switching Processes in Queueing Models. ISTE Ltd. (2008)
Samoilenko, I.V.: Large deviations for random evolutions with independent increments in the scheme of \(\rm L\)évy approximation with split and double merging. Random Oper. Stochast. Eqn. 22(2), 137–149 (2015)
Lebedev, E.O., Livinska, G.V.: On the asymptotic merging of the set of nodes in stochastic networks. Theor. Probab. Math. Stat. 101, 147–156 (2019)
Lebedev, E., Livinska, G.: Gaussian approximation of multi-channel networks in heavy traffic. In: Dudin, A., Klimenok, V., Tsarenkov, G., Dudin, S. (eds.) BWWQT 2013. CCIS, vol. 356, pp. 122–130. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-35980-4_14
Lebedev, E., Chechelnitsky, A., Livinska, G.: Multi-channel network with interdependent input flows in heavy traffic. Theor. Probab. Math. Stat. 97, 109–119 (2017)
Livinska, H., Lebedev, E.: On transient and stationary regimes for multi-channel networks with periodic inputs. Appl. Stat. Comput. 319, 13–23 (2018)
Lebedev, E., Makushenko, I.: Profit maximization and risk minimization in semi-Markovian networks. Cybern. Syst. Anal. 43(2), 213–224 (2007). https://doi.org/10.1007/s10559-007-0040-z
Korolyuk, V.S., Korolyuk, V.V.: Stochastic Models of Systems. Kluwer Acad. Press, Dordrecht (1999)
Scorokhod, A.V.: Lectures on the Theory of Stochastic Processes. Lybid, Kyiv (1990). (in Ukrainian)
Lebedev, E.O.: A limit theorem for stochastic networks and its application. Theor. Probab. Math. Stat. 68, 81–92 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Lebedev, E.A., Livinska, H. (2021). Reducing of Service Process Dimension for a General-Type Multichannel Network in Heavy Traffic. In: Dudin, A., Nazarov, A., Moiseev, A. (eds) Information Technologies and Mathematical Modelling. Queueing Theory and Applications. ITMM 2020. Communications in Computer and Information Science, vol 1391. Springer, Cham. https://doi.org/10.1007/978-3-030-72247-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-72247-0_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-72246-3
Online ISBN: 978-3-030-72247-0
eBook Packages: Computer ScienceComputer Science (R0)