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State-dependent M/G/1 queueing systems

Author

Listed:
  • Hossein Abouee-Mehrizi

    (University of Waterloo)

  • Opher Baron

    (University of Toronto)

Abstract

We consider a state-dependent $$M_{n}$$ M n / $$G_{n}$$ G n /1 queueing system with both finite and infinite buffer sizes. We allow the arrival rate of customers to depend on the number of people in the system. Service times are also state dependent and service rates can be modified at both arrivals and departures of customers. We show that the steady-state solution of this system at arbitrary times can be derived using the supplementary variable method, and that the system’s state at arrival epochs can be analyzed using an embedded Markov chain. For the system with infinite buffer size, we first obtain an expression for the steady-state distribution of the number of customers in the system at both arbitrary and arrival times. Then, we derive the average service time of a customer observed at both arbitrary times and arrival epochs. We show that our state-dependent queueing system is equivalent to a Markovian birth-and-death process. This equivalency demonstrates our main insight that the $$M_{n}$$ M n / $$G_{n}$$ G n /1 system can be decomposed at any given state as a Markovian queue. Thus, many of the existing results for systems modeled as an M / M / 1 queue can be carried through to the much more practical M / G / 1 model with state-dependent arrival and service rates. Then, we extend the results to the $$M_{n}$$ M n / $$G_{n}$$ G n /1 queueing systems with finite buffer size.

Suggested Citation

  • Hossein Abouee-Mehrizi & Opher Baron, 2016. "State-dependent M/G/1 queueing systems," Queueing Systems: Theory and Applications, Springer, vol. 82(1), pages 121-148, February.
  • Handle: RePEc:spr:queues:v:82:y:2016:i:1:d:10.1007_s11134-015-9461-y
    DOI: 10.1007/s11134-015-9461-y
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    References listed on IDEAS

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    Cited by:

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    4. Yuan, Xuchuan & Brian Hwarng, H., 2023. "Examining the dynamics of reactive capacity allocation through a chaos lens," European Journal of Operational Research, Elsevier, vol. 308(2), pages 912-928.

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