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Mathematics
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Mathematics
Article . 2025
Data sources: DOAJ
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Accurate Approximation for Resource Queuing Systems with Losses and Signals

Authors: Alexander Maslov; Eduard Sopin; Konstantin Samouylov;

Accurate Approximation for Resource Queuing Systems with Losses and Signals

Abstract

We consider a queuing system with a finite number of servers and a finite pool of resources, where an arriving customer requires a server and random number of resources. During the service, each customer is associated with a Poisson flow of “signals”, where upon a signal arrival, the currently allocated resources for a customer are released, and an attempt is made to allocate a new random amount of resources. Recently, such systems have received significant attention for their use in the analysis of 5G/6G cellular systems with non-elastic traffic demands and blockage impairments. Such queuing systems do not allow closed-form analytical solutions, and are conventionally solved using numerical methods. These methods are sensitive to the dimensions of the state space and can lead to inaccuracies. In this paper, we propose a new method for the approximate analysis of performance metrics in resource systems with signals using analytical solutions for similar systems without signals. Our detailed comparison with simulations shows that the relative error is limited to 5–10% over a wide range of system and load parameters.

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Keywords

QA1-939, 5G network, loss probability, termination probability, embedded Markov chain, resource loss system, Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Top 10%
Top 10%
Average
gold