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

• Evaluates performance metrics:

  • interval: arrival interval, departure interval

  • delay: waiting time, queue length

  • age of information: mean age, peak age, effective departing ratio

• Scheduling polices are categorised based on

  • FCFS or LCFS

  • Preemptive or Non-Preemptive

  • Priority or Non-Priority: arrivals with different priorities

  • Size-based or not: SRPT (shortest-remaining-processing-time)

  • Age-based or not: SEA (shortest-expected-age) not available right now

• Scheduling polices supported:

  • FCFS

  • FCFSPriority: FCFS + Priority

  • FCFSSRPT: FCFS + SRPT

  • FCFSSEA: FCFS + SEA

  • LCFS:

  • Pre-LCFS: LCFS + Preemptive

  • LCFSPriority: LCFS + Priority

  • LCFSSRPT: LCFS + SRPT

  • LCFSSEA: LCFS + SEA

How the code works

run the file, main.py