A Discrete-Time Single-Server Retrial Queue with Preemption and Adaptive Retrial Times: Theoretical Analysis and Telecommunication Insights

This paper analyzes a discrete-time single-server retrial queue with preemptive service, Bernoulli arrivals, and adaptive retrial times, tailored to telecommunications systems. In call centers, the model captures caller retries and priority interruptions, while in cellular networks, it represents user channel access attempts with preemption for emergency calls. Using a Markov chain framework, we derive the stationary distribution, establish a stability condition, and compute performance metrics, including the mean number of retrying callers or users and orbit size probabilities. The model incorporates a novel retrial time adaptation probability, reflecting dynamic retry behaviors in telecommunications. Numerical results demonstrate the impact of arrival rates, preemption probabilities, and retrial adaptations on system performance, offering insights for optimizing call center staffing and cellular network protocols. Applications to slotted ALOHA and TDMA systems highlight the model’s practical relevance.

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Publication Details

Journal
Mathematics
Published
2025-10-22
DOI
https://doi.org/10.3390/math13213361
Primary Topic
Advanced Queuing Theory Analysis
Type
article
Field-Weighted Citation Impact
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article

A Discrete-Time Single-Server Retrial Queue with Preemption and Adaptive Retrial Times: Theoretical Analysis and Telecommunication Insights

Mathematics
Advanced Queuing Theory Analysis
article

A Discrete-Time Single-Server Retrial Queue with Preemption and Adaptive Retrial Times: Theoretical Analysis and Telecommunication Insights

article en

Abstract

This paper analyzes a discrete-time single-server retrial queue with preemptive service, Bernoulli arrivals, and adaptive retrial times, tailored to telecommunications systems. In call centers, the model captures caller retries and priority interruptions, while in cellular networks, it represents user channel access attempts with preemption for emergency calls. Using a Markov chain framework, we derive the stationary distribution, establish a stability condition, and compute performance metrics, including the mean number of retrying callers or users and orbit size probabilities. The model incorporates a novel retrial time adaptation probability, reflecting dynamic retry behaviors in telecommunications. Numerical results demonstrate the impact of arrival rates, preemption probabilities, and retrial adaptations on system performance, offering insights for optimizing call center staffing and cellular network protocols. Applications to slotted ALOHA and TDMA systems highlight the model’s practical relevance.

MathematicsVol. 13(21)
Universidad de Málaga (ES)
Openalex Percentile: Top 32%
Advanced Queuing Theory Analysis
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