AgeQueueing
A queueing simulator implemented on Python. It evaluates queueing performance metrics including Age-of-Information (AoI) under different scheduling policies in a Monte Carlo way.
The project includes:
- queueengine.py: the QUEUE class, including all kinds of queueing operations, such as arriving, waiting, serving, and departing.
- main.py: run this file, including setting queueing parameters, conducting different simulations, saving data and plotting curves.
Required packages
- Python 3.*
- numpy
- pandas
- matplotlib
What it can do
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Evaluates performance metrics:
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interval: arrival interval, departure interval
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delay: waiting time, queue length
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age of information: mean age, peak age, effective departing ratio
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Scheduling polices are categorised based on
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FCFS or LCFS
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Preemptive or Non-Preemptive
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Priority or Non-Priority: arrivals with different priorities
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Size-based or not: SRPT (shortest-remaining-processing-time)
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Age-based or not: SEA (shortest-expected-age) not available right now
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Scheduling polices supported:
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FCFS
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FCFSPriority: FCFS + Priority
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FCFSSRPT: FCFS + SRPT
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FCFSSEA: FCFS + SEA
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LCFS:
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Pre-LCFS: LCFS + Preemptive
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LCFSPriority: LCFS + Priority
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LCFSSRPT: LCFS + SRPT
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LCFSSEA: LCFS + SEA
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How the code works
run the file, main.py