M-M-1-K-simulator-ProcessSharing

M/M/1/K with process sharing server analytical and simulation implementation

According to ْassumtions arrivals follow a Poisson process while job service time is an exponential distribution.Simulation is implemented as simulation.py and analytical approach is implemented by analyze.py and all you need to simulate is to run the main.py file.

Input

parameters.conf first line is Teta and second line is Mu.

Output

Analytical and simulation result for lambda = [5,10,15] is stored within result.csv according to the following header :

• Teta

• Mu

• Lambda

• Analysis_type

• PB

• PD

Objects

Event

Event object includes three attribute:

• Time

• Process ID

• Type :

  1. Arrival

  2. Departure

  3. Deadline

• Start time

• Queue size

Process

Process Objects has following attributes:

• Process ID

• Arrival

• Deadline

• Service Time