Virtual Labs

How does the assumption of general service time distributions (M/G/1/N) differ from assuming exponential service times (M/M/1/N) in a queueing system?

a: M/G/1/N model allows for more flexible analysis of non-exponential service times Explanation

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b: M/M/1/N model guarantees shorter waiting times Explanation

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c: M/G/1/N model always results in higher system utilization Explanation

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d: M/M/1/N model is more suitable for high arrival rate scenarios Explanation

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How does the finite system capacity 'N' affect the trade-off between waiting time and system utilization?

a: Higher 'N' results in shorter waiting times but lower system utilization Explanation

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b: Lower 'N' leads to higher system stability but longer waiting times Explanation

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c: Higher 'N' always ensures higher system utilization Explanation

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d: System utilization remains unaffected by the value of 'N' Explanation

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How does variability in arrival rates impact the behavior of an M/G/1/N queueing system?

a: Higher variability always leads to longer waiting times Explanation

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b: Lower variability guarantees higher system stability Explanation

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c: Variability does not affect system performance Explanation

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d: Variability may result in unpredictable system behavior Explanation

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