diff --git a/.gitignore b/.gitignore index 9a9c0be..086bb48 100644 --- a/.gitignore +++ b/.gitignore @@ -10,5 +10,3 @@ *build* test/output/* /.idea/* - -assignment_output/ \ No newline at end of file diff --git a/assignment/.gitignore b/assignment/.gitignore deleted file mode 100644 index 9f3731b..0000000 --- a/assignment/.gitignore +++ /dev/null @@ -1 +0,0 @@ -*_solution.py \ No newline at end of file diff --git a/assignment/atomicdevs.py b/assignment/atomicdevs.py deleted file mode 100644 index f462b69..0000000 --- a/assignment/atomicdevs.py +++ /dev/null @@ -1,91 +0,0 @@ - -### EDIT THIS FILE ### - -from pypdevs.DEVS import AtomicDEVS -from environment import * -import random -import dataclasses - -class Queue(AtomicDEVS): - def __init__(self, ship_sizes): - super().__init__("Queue") - # self.state = QueueState(...) - - # def extTransition(self, inputs): - # pass - - # def timeAdvance(self): - # pass - - # def outputFnc(self): - # pass - - # def intTransition(self): - # pass - -PRIORITIZE_BIGGER_SHIPS = 0 -PRIORITIZE_SMALLER_SHIPS = 1 - -class RoundRobinLoadBalancer(AtomicDEVS): - def __init__(self, - lock_capacities=[3,2], # two locks of capacities 3 and 2. - priority=PRIORITIZE_BIGGER_SHIPS, - ): - super().__init__("RoundRobinLoadBalancer") - # self.state = LoadBalancerState(...) - - # def extTransition(self, inputs): - # pass - - # def timeAdvance(self): - # pass - - # def outputFnc(self): - # pass - - # def intTransition(self): - # pass - -class FillErUpLoadBalancer(AtomicDEVS): - def __init__(self, - lock_capacities=[3,2], # two locks of capacities 3 and 2. - priority=PRIORITIZE_BIGGER_SHIPS, - ): - super().__init__("FillErUpLoadBalancer") - # self.state = LoadBalancerState(...) - - # def extTransition(self, inputs): - # pass - - # def timeAdvance(self): - # pass - - # def outputFnc(self): - # pass - - # def intTransition(self): - # pass - -class Lock(AtomicDEVS): - def __init__(self, - capacity=2, # lock capacity (2 means: 2 ships of size 1 will fit, or 1 ship of size 2) - max_wait_duration=60.0, - passthrough_duration=60.0*15.0, # how long does it take for the lock to let a ship pass through it - ): - super().__init__("Lock") - # self.state = LockState(...) - - # def extTransition(self, inputs): - # pass - - # def timeAdvance(self): - # pass - - # def outputFnc(self): - # pass - - # def intTransition(self): - # pass - - -### EDIT THIS FILE ### diff --git a/assignment/doc/assignment.html b/assignment/doc/assignment.html deleted file mode 100644 index 1aa013d..0000000 --- a/assignment/doc/assignment.html +++ /dev/null @@ -1,234 +0,0 @@ - - -

Practical stuff

- - -

Introduction

-

You will use (classic) DEVS to model a queueing and load balancing system for a set of waterway locks. A conceptual view of the system is shown here:

- -

Ships move in the direction of the arrows. A generator generates ships at pseudo-random time intervals, which are added to a queue. Whenever the queue has a ship available, and one of the locks has enough remaining capacity for that ship, the load balancer pulls a ship from the queue and sends it to that lock. A lock may fit more than one ship, so as long as it is not filled up to full capacity, it may wait for more ships to arrive before the lock doors close and the ships can pass through to the other side of the lock. At the end of the system, we have a Sink, where all ships are collected, so we can extract statistics to analyse performance.

- -

Ships can have different sizes. For simplicity, the size of a ship is a small integer (e.g., 1 or 2). Locks can have different capacities: for instance, a lock of capacity 3 will fit either: -

-

- -

Specification

- -

We now give an overview of the different DEVS components, and their behavior, and their parameters. Although many of the parameters are fixed, your solution must work with different parameters as well. In other words, don't hardcode the parameter values in your DEVS blocks!

- -

Atomic DEVS blocks

- - -

The specification of the semantics of the Atomic DEVS blocks is entirely deterministic. If you implement everything correctly, the system as-a-whole will behave 100% identical to the teacher's solution.

- -

Coupled DEVS

-

The system as a whole is modeled as a Coupled DEVS block. Its parameters are mostly passed as-is to the underlying Atomic DEVS blocks. They are: -

-

- -

What is expected

-

First of all, you are given an implementation of the following AtomicDEVS blocks, which you must not edit:

- -

You will:

- -

An indication of the complexity: my own solution of the AtomicDEVS blocks is about 300 lines of code (including comments).

- -

Goal: Performance Analysis

-

Once you have implemented the system, we will do performance analysis, comparing combinations of the following parameter values:

- -

More specifically, we would like to know under which (combinations of) parameter values the (avg/min/max) duration that ships spend in the system is minimized. Also, we'd like to know if one choice (e.g., prioritize bigger) always better than another choice (e.g., prioritize smaller), or does it depend on the choices made for the other parameters?

- -

Getting Started

-
    -
  1. Clone the mosis24 branch of this git repository.
    2. -
  2. Under the assignment directory, you'll find the following files: -
      -
    • runner.py This script runs the simulation for all combinations of parameter values as described in the Performance Analysis section. It will generate .csv files with the time durations that each ship has spent in the system. Every row is a ship (500 ships, so 500 rows total), and every column represents a different value for the max_wait_duration parameter. It will also generate a plot.gnuplot file, which you can run with gnuplot as follows: - 
      gnuplot plot.gnuplot
      - which will result in a number of SVG files containing plots of the CSV files. - -

      You are only allowed to make temporary changes (for debugging) to this file.

      -
      • -
    • system.py Contains the full system, modeled as CoupledDEVS. You need to edit this file.
      • -
    • atomicdevs.py Contains skeletons for the AtomicDEVS blocks that you must implement. You need to edit this file.
      • -
    • environment.py Contains implementations of the Generator, Sink and Ship types. You must not edit this file.
      • -
    -
    3. -
  3. Write a report, where you: -
      -
    • explain and motivate the interfaces/protocol of the AtomicDEVS blocks
      • -
    • show the plotted results
      • -
    • interpret the plotted results
      • -
    -
    4. -
  4. Submit via BlackBoard, a ZIP file, containing: -
      -
    • Your code (only the assignment directory)
      • -
    • Your report (PDF)
      • -
    • The generated CSV- and SVG-files
      • -
    -
    5. -
  5. Deadline: Sunday 5 December 2025, 23:59
    6. -
- -

Attention!

-

You must stick to the rules of DEVS:

- -

Any violation of these rules results in an incorrect solution. Points will be subtracted.

- -

Coding Conventions

- -

Please follow these coding conventions:

- - -

Tips

- - -

Troubleshooting

- -

Common mistakes include: -

-

- -

Extra Material

- - - \ No newline at end of file diff --git a/assignment/doc/concept.svg b/assignment/doc/concept.svg deleted file mode 100644 index df2edf2..0000000 --- a/assignment/doc/concept.svg +++ /dev/null @@ -1,3 +0,0 @@ - - -
Generator
Queue
Load Balancer
Lock
Lock
Sink
 \ No newline at end of file diff --git a/assignment/doc/figures.drawio b/assignment/doc/figures.drawio deleted file mode 100644 index fd69eb1..0000000 --- a/assignment/doc/figures.drawio +++ /dev/null @@ -1,61 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - diff --git a/assignment/environment.py b/assignment/environment.py deleted file mode 100644 index 27617d2..0000000 --- a/assignment/environment.py +++ /dev/null @@ -1,98 +0,0 @@ - -### DO NOT EDIT THIS FILE ### - -from pypdevs.DEVS import AtomicDEVS -import random -import dataclasses - -# The reason for annotating the *State-classes as 'dataclass', is because this automatically generates a nice __repr__-function, so that if the simulator is set to verbose, you can actually see what the state is. - -class Ship: - def __init__(self, size, creation_time): - self.size = size - self.creation_time = creation_time - - # useful in verbose mode: - def __repr__(self): - return f"Ship(size={self.size},created={self.creation_time})" - -@dataclasses.dataclass -class GeneratorState: - current_time: float - time_until_next_ship: float - to_generate: int - random: random.Random - - def __init__(self, seed=0, gen_num=1000): - self.current_time = 0.0 # for statistics only - self.time_until_next_ship = 0.0 - self.to_generate = gen_num - self.random = random.Random(seed) - -class Generator(AtomicDEVS): - def __init__(self, - seed=0, # random seed - lambd=1.0/60.0, # how often to generate a ship - in this example, once per minute - gen_types=[1,1,2], # ship sizes to generate, will be sampled uniformly - in this example, size 1 is twice as likely as size 2. - gen_num=1000, # number of ships total to generate - ): - super().__init__("Generator") - - # State (for everything that is mutable) - self.state = GeneratorState(seed=seed, gen_num=gen_num) - - # I/O - self.out_ship = self.addOutPort("out_event") - - # Parameters (read-only) - self.lambd = lambd - self.gen_types = gen_types - - def timeAdvance(self): - return self.state.time_until_next_ship - - def outputFnc(self): - size = self.state.random.choice(self.gen_types) # uniformly sample from gen_types - # watch out: outputFnc is called *before* intTransition! - creation = self.state.current_time + self.state.time_until_next_ship - return { self.out_ship: Ship(size, creation) } - - def intTransition(self): - self.state.current_time += self.state.time_until_next_ship - self.state.to_generate -= 1 - if self.state.to_generate > 0: - self.state.time_until_next_ship = self.state.random.expovariate(self.lambd) - else: - # stop generating - self.state.time_until_next_ship = float('inf') - return self.state - -@dataclasses.dataclass -class SinkState: - current_time: float - ships: list - - def __init__(self): - self.current_time = 0.0 - self.ships = [] - -class Sink(AtomicDEVS): - def __init__(self): - super().__init__("Sink") - self.state = SinkState() - - # On this input port, the Sink expects to receive a *list* of Ships. This is because a Lock can contain more than one Ship, and the Lock can send them all at once to the Sink (with a single event). - self.in_ships = self.addInPort("in_ships") - - def extTransition(self, inputs): - self.state.current_time += self.elapsed - if self.in_ships in inputs: - ships = inputs[self.in_ships] - for ship in ships: - ship.finished_time = self.state.current_time - # amount of time spent in the system: - ship.queueing_duration = ship.finished_time - ship.creation_time - self.state.ships.extend(ships) - return self.state - -### DO NOT EDIT THIS FILE ### diff --git a/assignment/plot_template.py b/assignment/plot_template.py deleted file mode 100644 index bf1b595..0000000 --- a/assignment/plot_template.py +++ /dev/null @@ -1,86 +0,0 @@ -def make_plot_ships_script(priority:str, strategy:str, max_waits:list[float], gen_num:int): - return (f""" -### priority={priority}, strategy={strategy} ### - -set terminal svg size 1200 900 - -# plot 1. x-axis: ships, y-axis: queuing duration of ship - -set out 'plot_ships_{strategy}_{priority}.svg' -set title "Queueing duration (strategy={strategy}, priority={priority})" -set xlabel "Ship #" -set ylabel "Seconds" -#unset xlabel -#unset xtics -set key title "Max Wait" -set key bottom center out -set key horizontal - -""" -# + '\n'.join([ -# f"set style line {i+1} lw 4" -# for i in range(len(max_waits)) -# ]) - + f""" - -# set yrange [0:90000] -set xrange [0:{gen_num}] -set style fill solid - -plot 'output_{strategy}_{priority}.csv' \\\n """ + ", \\\n '' ".join([ - f"using 1:{i+2} title '{max_wait}' w boxes ls {i+1}" - for i, max_wait in enumerate(max_waits) -])) - -def make_plot_box_script(priority:str, strategy:str, max_waits:list[float], gen_num:int): - return (f""" - -# plot 2. x-axis: max-wait parameter, y-axis: queueing durations of ships - -set out 'plot_box_{strategy}_{priority}.svg' -set title "Queueing duration (strategy={strategy}, priority={priority})" -set style fill solid 0.25 border -1 -set style boxplot outliers pointtype 7 -set style data boxplot -set key off - -set xlabel "Max Wait" -unset xrange -unset yrange - -set xtics (""" + ', '.join([ f"'{max_wait}' {i}" - for i, max_wait in enumerate(max_waits)]) + f""") - -plot 'output_{strategy}_{priority}.csv' \\\n """ + ", \\\n '' ".join([ - f"using ({i}):{i+2} title '{max_wait}'" - for i, max_wait in enumerate(max_waits) -])) - -def make_plot_frequency_script(priority:str, strategy:str, max_waits:list[float], gen_num:int): - return (f""" - -# plot 3. x-axis: queueing duration interval, y-axis: number of ships - -bin_width = 5*60; - -set out 'plot_freq_{strategy}_{priority}.svg' -set title "Frequency of queueing durations (strategy={strategy}, priority={priority})" -set boxwidth (bin_width) absolute -set style fill solid 1.0 noborder - -set key title "Max Wait" -set key bottom center out -# set key horizontal - -set xtics auto -set xrange [0:] -set xlabel "Queueing duration (interval)" -set ylabel "Number of ships" - -bin_number(x) = floor(x/bin_width) -rounded(x) = bin_width * ( bin_number(x) + 0.5 ) - -plot 'output_{strategy}_{priority}.csv' \\\n """ + ", \\\n '' ".join([ - f"using (rounded(${i+2})):(1) title '{max_wait}' smooth frequency with boxes" - for i, max_wait in list(enumerate(max_waits)) -])) diff --git a/assignment/runner.py b/assignment/runner.py deleted file mode 100644 index 6b840a6..0000000 --- a/assignment/runner.py +++ /dev/null @@ -1,106 +0,0 @@ -import os - -from pypdevs.simulator import Simulator -from plot_template import make_plot_ships_script, make_plot_box_script, make_plot_frequency_script - -# from system_solution import * # Teacher's solution -from system import * - -## Parameters ## - -gen_num = 500 # how many ships to generate - -# How often to generate a ship (on average) -gen_rate = 1/60/4 # once every 4 minutes - -# Ship size will be sampled uniformly from the following list. -gen_types = [1,1,2] # ship size '1' twice as likely to be generated as ship size '2' - -# Load balancer... -priorities = { - # you can outcomment one of these lines to reduce the number of experiments (useful for debugging): - PRIORITIZE_BIGGER_SHIPS: "bigger", - PRIORITIZE_SMALLER_SHIPS: "smaller", -} -strategies = { - # you can outcomment one of these lines to reduce the number of experiments (useful for debugging): - STRATEGY_ROUND_ROBIN: "roundrobin", - STRATEGY_FILL_ER_UP: "fillerup", -} - -# The number of locks and their capacities -lock_capacities=[3,2] # two locks, of capacity 3 and 2 - -# The different parameters to try for max_wait_duration -max_wait_durations = [ 0.0+i*120.0 for i in range(5) ] # all these values will be attempted -# max_wait_durations = [ 15.0 ] # <-- uncomment if you only want to run an experiment with this value (useful for debugging) - -# How long does it take for a ship to pass through a lock -passthrough_duration = 60.0*15 # 15 minutes - -outdir = "assignment_output" - -plots_ships = [] -plots_box = [] -plots_freq = [] - -os.makedirs(outdir, exist_ok=True) - -# try all combinations of priorities and strategies (4 total) -for priority in priorities: - for strategy in strategies: - values = [] - # and in each experiment, try a bunch of different values for the 'max_wait_duration' parameter: - for max_wait_duration in max_wait_durations: - print("Run simulation:", priorities[priority], strategies[strategy], "max_wait =",max_wait_duration) - sys = LockQueueingSystem( - # See system.py for explanation of these values: - seed=0, - gen_num=gen_num, - gen_rate=gen_rate, - gen_types=gen_types, - load_balancer_strategy=strategy, - lock_capacities=lock_capacities, - priority=priority, - max_wait_duration=max_wait_duration, - passthrough_duration=passthrough_duration, - ) - sim = Simulator(sys) - sim.setClassicDEVS() - # sim.setVerbose() # <-- uncomment to see what's going on - sim.simulate() - - # all the ships that made it through - ships = sys.sink.state.ships - values.append([ship.queueing_duration for ship in ships]) - - # Write out all the ship queueuing durations for every 'max_wait_duration' parameter - # for every ship, we write a line: - # , time_max_wait0, time_max_wait1, time_max_wait2, ... time_max_wait10 - filename = f'{outdir}/output_{strategies[strategy]}_{priorities[priority]}.csv' - with open(filename, 'w') as f: - try: - for i in range(gen_num): - f.write("%s" % i) - for j in range(len(values)): - f.write(", %5f" % (values[j][i])) - f.write("\n") - except IndexError as e: - raise Exception("There was an IndexError, meaning that fewer ships have made it to the sink than expected.\nYour model is not (yet) correct.") from e - - # Generate gnuplot code: - for f, col in [(make_plot_ships_script, plots_ships), (make_plot_box_script, plots_box), (make_plot_frequency_script, plots_freq)]: - col.append(f( - priority=priorities[priority], - strategy=strategies[strategy], - max_waits=max_wait_durations, - gen_num=gen_num, - )) - -# Finally, write out a single gnuplot script that plots everything -with open(f'{outdir}/plot.gnuplot', 'w') as f: - # first plot the ships - f.write('\n\n'.join(plots_ships)) - # then do the box plots - f.write('\n\n'.join(plots_box)) - f.write('\n\n'.join(plots_freq)) diff --git a/assignment/system.py b/assignment/system.py deleted file mode 100644 index f55d645..0000000 --- a/assignment/system.py +++ /dev/null @@ -1,65 +0,0 @@ - -### EDIT THIS FILE ### - -from pypdevs.DEVS import CoupledDEVS -from atomicdevs import * - -STRATEGY_ROUND_ROBIN = 0 -STRATEGY_FILL_ER_UP = 1 - -class LockQueueingSystem(CoupledDEVS): - def __init__(self, - # See runner.py for an explanation of these parameters!! - seed, - gen_num, - gen_rate, - gen_types, - load_balancer_strategy, - lock_capacities, - priority, - max_wait_duration, - passthrough_duration, - ): - super().__init__("LockQueueingSystem") - - # Instantiate sub-models with the right parameters, and add them to the CoupledDEVS: - - generator = self.addSubModel(Generator( - seed=seed, # random seed - lambd=gen_rate, - gen_types=gen_types, - gen_num=gen_num, - )) - - queue = self.addSubModel(Queue( - ship_sizes=set(gen_types), # the queue only needs to know the different ship sizes (and create a FIFO queue for each) - )) - - if load_balancer_strategy == STRATEGY_ROUND_ROBIN: - LoadBalancer = RoundRobinLoadBalancer - elif load_balancer_strategy == STRATEGY_FILL_ER_UP: - LoadBalancer = FillErUpLoadBalancer - - load_balancer = self.addSubModel(LoadBalancer( - lock_capacities=lock_capacities, - priority=priority, - )) - - locks = [ self.addSubModel(Lock( - capacity=lock_capacity, - max_wait_duration=max_wait_duration, - passthrough_duration=passthrough_duration)) - for lock_capacity in lock_capacities ] - - sink = self.addSubModel(Sink()) - - # Don't forget to connect the input/output ports of the different sub-models: - # for instance: - # self.connectPorts(generator.out_ship, queue.in_ship) - # ... - - # Our runner.py script needs access to the 'sink'-state after completing the simulation: - self.sink = sink - - -### EDIT THIS FILE ### diff --git a/examples/queueing/experiment.py b/examples/queueing/experiment.py index 71e0f5d..0d47421 100644 --- a/examples/queueing/experiment.py +++ b/examples/queueing/experiment.py @@ -1,4 +1,5 @@ from pypdevs.simulator import Simulator +import random # Import the model we experiment with from system import QueueSystem @@ -21,6 +22,7 @@ values = [] # Loop over different configurations for i in range(1, max_processors): # Make sure each of them simulates exactly the same workload + random.seed(1) # Set up the system procs = [speed] * i m = QueueSystem(mu=1.0/time, size=size, num=num, procs=procs) @@ -28,7 +30,6 @@ for i in range(1, max_processors): # PythonPDEVS specific setup and configuration sim = Simulator(m) sim.setClassicDEVS() - sim.setVerbose() # <- uncomment to see what's going on sim.simulate() # Gather information for output diff --git a/examples/queueing/generator.py b/examples/queueing/generator.py index 05b1587..57423eb 100644 --- a/examples/queueing/generator.py +++ b/examples/queueing/generator.py @@ -1,17 +1,9 @@ from pypdevs.DEVS import AtomicDEVS from job import Job import random -import dataclasses # Define the state of the generator as a structured object -@dataclasses.dataclass class GeneratorState: - current_time: float - remaining: float - to_generate: int - next_job: None - random: random.Random - def __init__(self, gen_num, seed=0): # Current simulation time (statistics) self.current_time = 0.0 @@ -42,22 +34,14 @@ class Generator(AtomicDEVS): # Determine size of the event to generate size = max(1, int(self.state.random.gauss(self.size_param, 5))) # Calculate current time (note the addition!) - creation = self.state.current_time + creation = self.state.current_time + self.state.remaining # Update state self.state.next_job = Job(size, creation) self.state.remaining = self.state.random.expovariate(self.gen_param) - def timeAdvance(self): - # Return remaining time; infinity when generated enough - return self.state.remaining - - def outputFnc(self): - # Output the new event on the output port - return {self.out_event: self.state.next_job} - def intTransition(self): # Update simulation time - self.state.current_time += self.state.remaining + self.state.current_time += self.timeAdvance() # Update number of generated events self.state.to_generate -= 1 if self.state.to_generate == 0: @@ -69,3 +53,10 @@ class Generator(AtomicDEVS): self.__nextJob() return self.state + def timeAdvance(self): + # Return remaining time; infinity when generated enough + return self.state.remaining + + def outputFnc(self): + # Output the new event on the output port + return {self.out_event: self.state.next_job} diff --git a/examples/queueing/job.py b/examples/queueing/job.py index d8ade30..54a7314 100644 --- a/examples/queueing/job.py +++ b/examples/queueing/job.py @@ -3,6 +3,3 @@ class Job: # Jobs have a size and creation_time parameter self.size = size self.creation_time = creation_time - - def __repr__(self): - return f"Job(size={self.size},creation_time={self.creation_time})" \ No newline at end of file diff --git a/examples/queueing/queue.py b/examples/queueing/queue.py index 8fbe89c..5b11cab 100644 --- a/examples/queueing/queue.py +++ b/examples/queueing/queue.py @@ -29,6 +29,20 @@ class Queue(AtomicDEVS): self.in_event = self.addInPort("in_event") self.in_finish = self.addInPort("in_finish") + def intTransition(self): + # Is only called when we are outputting an event + # Pop the first idle processor and clear processing event + self.state.idle_procs.pop(0) + if self.state.queue and self.state.idle_procs: + # There are still queued elements, so continue + self.state.processing = self.state.queue.pop(0) + self.state.remaining_time = self.processing_time + else: + # No events left to process, so become idle + self.state.processing = None + self.state.remaining_time = float("inf") + return self.state + def extTransition(self, inputs): # Update the remaining time of this job self.state.remaining_time -= self.elapsed @@ -59,17 +73,3 @@ class Queue(AtomicDEVS): # Output the event to the processor port = self.out_proc[self.state.idle_procs[0]] return {port: self.state.processing} - - def intTransition(self): - # Is only called when we are outputting an event - # Pop the first idle processor and clear processing event - self.state.idle_procs.pop(0) - if self.state.queue and self.state.idle_procs: - # There are still queued elements, so continue - self.state.processing = self.state.queue.pop(0) - self.state.remaining_time = self.processing_time - else: - # No events left to process, so become idle - self.state.processing = None - self.state.remaining_time = float("inf") - return self.state