Discrete Event Simulator

Assignment and final lab for "Distributed Computing" course.

Objective: simulate and analyze a distributed system

Note: all parameters are optional (having default values) unless stated otherwise.

SIR

Example for understanding system state and events

usage: python3 ./sir.py [--population] [--infected] [--seed] [--avg-contact-time] [--avg-recovery-time] [--verbose] [--plot_interval]

• --population: int the total population of individuals to simulate
• --infected: int starting number of infected people
• --seed: int random number generator seed
• --avg-contact-time: float average contact time between two individuals
• --avg-recovery-time: float average recovery time after infection
• --verbose: enable verbose mode
• --plot_interval: float data point collection frequency for the final plot

M/M/n queue

Simulation of a multi server FIFO queueign model.

• Jobs are spawned at a lambd rate and are competed with a mu probability.
• The simulation supports n multiple servers.
• Each spawned job is inserted using a so called "SuperMarket model" in the emptyest queue selected from a d subset of n
  • The SuperMarket model works just like when checking out at costco; you scan the nearest ~5 queues and select the one with less people waiting. In the same fashion, the supermarket model watches d severs (picked at random) and inserts the job in the queue with less jobs awaiting completion.

usage: python3 ./mmn_queue.py [--lambd] [--mu] [--max-t] [--n] [--d] [--csv]

• --lambd: float arrival rate of jobs
• --mu: float service rate of jobs
• --max-t: float maximum simulation time
• --n: int number of simulated servers
• --d: int number of servers to watch for the supermarket model
• --csv: str path to csv file to save the simulation data

Erasure Coding

To be implemented :(