Add probabilistic WCET feature

The aim of this commit is to add new feature for real time tasks simulator
'simso'. We allow WCET of a task to be defined as a discrete Probability
Distribution Function (PDF) using a matrix (numpy array) of two row: one
for possible WCET values and the other for their corresponding
probabilities. When the WCET of a task is defined as probability
distribution, the simulator will pick random value from the possible WCET
values proportionally to their probabilities. Then, it create a new job
that has as WCET the generated random value.

The modified files in this commit are:

    - simso/utils/probabilistic_calc.py: new file contain function that
    generate random value according to a probability distribution.
    - simso/configuration/Configuration.py: In case of probabilistic
    WCET, verify that all WCET values are positive and that
    probabilities sum to one.
    - simso/core/Job.py: define new attribute '_wcet' individual value
    for each job instance.
    - simso/core/Task.py: In case of probabilistic WCET, generate random
    value of WCET using 'randon_int_from_distr' function from
    'probabilistic_calc.py' module. Then, create  new job with
    the generated WCET.
    - simso/core/__init__.py: change import order to avoid program crush.

misc/script.py file is also slightly modified to add a task 'T1' with
probabilistic WCET. When run, this script will generate a scheduling where
several instance of task 'T1' has different WCET values.

Author: Slim Ben Amor

misc/script.py

@@ -7,6 +7,7 @@
 import sys
 from simso.core import Model
 from simso.configuration import Configuration
+import numpy as np
 
 
 def main(argv):
@@ -21,7 +22,7 @@ def main(argv):
 
         # Add tasks:
         configuration.add_task(name="T1", identifier=1, period=7,
-                               activation_date=0, wcet=3, deadline=7)
+                               activation_date=0, wcet=np.array([[1,2,3],[.1,.2,.7]]), deadline=7)   # add a task with a probabilistic WCET
         configuration.add_task(name="T2", identifier=2, period=12,
                                activation_date=0, wcet=3, deadline=12)
         configuration.add_task(name="T3", identifier=3, period=20,

simso/configuration/Configuration.py

@@ -4,6 +4,7 @@
 import os
 import re
 from xml.dom import minidom
+import numpy as np
 from simso.core.Scheduler import SchedulerInfo
 from simso.core import Scheduler
 from simso.core.Task import TaskInfo
@@ -181,22 +182,33 @@ def check_tasks(self):
                 "name must begins with a letter and must not contains any "\
                 "special character."
 
-            # Activation date >= 0:
+            # Activation date >= 0:
             assert task.activation_date >= 0, \
                 "Activation date must be positive."
 
             # Period >= 0:
             assert task.period >= 0, "Tasks' periods must be positives."
 
-            # Deadline >= 0:
+            # Deadline >= 0:
             assert task.deadline >= 0, "Tasks' deadlines must be positives."
 
             # N_instr >= 0:
             assert task.n_instr >= 0, \
                 "A number of instructions must be positive."
 
-            # WCET >= 0:
-            assert task.wcet >= 0, "WCET must be positive."
+            # WCET >= 0:
+            if isinstance(task.wcet, np.ndarray):
+                assert np.min(task.wcet[0, :]) >= 0, "WCETs must be positive"
+                assert np.sum(task.wcet[1, :]) == 1, "probabilities sum must be 1"
+            else:
+                assert task.wcet >= 0, "WCET must be positive."
+                if self.etm == "cache":
+                    # stack
+                    assert task.stack_file, "A task needs a stack profile."
+
+                    # stack ok
+                    assert task.csdp, "Stack not found or empty."
+
 
             # ACET >= 0:
             assert task.acet >= 0, "ACET must be positive."
@@ -209,13 +221,6 @@ def check_tasks(self):
             assert 0.0 <= task.mix <= 2.0, \
                 "A mix must be positive and less or equal than 2.0"
 
-            if self.etm == "cache":
-                # stack
-                assert task.stack_file, "A task needs a stack profile."
-
-                # stack ok
-                assert task.csdp, "Stack not found or empty."
-
     def check_caches(self):
         for index, cache in enumerate(self._caches_list):
             # Id unique :
@@ -231,7 +236,7 @@ def check_caches(self):
             # Taille positive :
             assert cache.size >= 0, "A cache size must be positive."
 
-            # Access time >= 0:
+            # Access time >= 0:
             assert cache.access_time >= 0, "An access time must be positive."
 
     def get_hyperperiod(self):

simso/core/Job.py

@@ -9,7 +9,7 @@ class Job(Process):
     """The Job class simulate the behavior of a real Job. This *should* only be
     instantiated by a Task."""
 
-    def __init__(self, task, name, pred, monitor, etm, sim):
+    def __init__(self, task, name, pred, monitor, etm, sim, wcet=None):
         """
         Args:
             - `task`: The parent :class:`task <simso.core.Task.Task>`.
@@ -44,6 +44,7 @@ def __init__(self, task, name, pred, monitor, etm, sim):
         self._monitor = monitor
         self._etm = etm
         self._was_running_on = task.cpu
+        self._wcet = wcet
 
         self._on_activate()
 
@@ -243,7 +244,9 @@ def wcet(self):
         Worst-Case Execution Time in milliseconds.
         Equivalent to ``self.task.wcet``.
         """
-        return self._task.wcet
+        if (self._wcet is None):
+            return self._task.wcet
+        return self._wcet
 
     @property
     def activation_date(self):
@@ -291,7 +294,7 @@ def activate_job(self):
             # Wait an execute order.
             yield passivate, self
 
-            # Execute the job.
+            # Execute the job.
             if not self.interrupted():
                 self._on_execute()
                 # ret is a duration lower than the remaining execution time.

simso/core/Task.py

@@ -2,8 +2,10 @@
 
 from collections import deque
 from SimPy.Simulation import Process, Monitor, hold, passivate
+import numpy as np
 from simso.core.Job import Job
 from simso.core.Timer import Timer
+from simso.utils.probabilistic_calc import random_int_from_distr
 from .CSDP import CSDP
 
 import os
@@ -272,9 +274,15 @@ def create_job(self, pred=None):
         directly by a scheduler.
         """
         self._job_count += 1
-        job = Job(self, "{}_{}".format(self.name, self._job_count), pred,
-                  monitor=self._monitor, etm=self._etm, sim=self.sim)
 
+        # pick random wcet according to their probabilities
+        if isinstance(self.wcet, np.ndarray):
+            wcet_sample = random_int_from_distr(self.wcet, n_sample=1)[0] 
+        else:
+            wcet_sample = None
+
+        job = Job(self, "{}_{}".format(self.name, self._job_count), pred,
+                  monitor=self._monitor, etm=self._etm, sim=self.sim, wcet=wcet_sample)
         if len(self._activations_fifo) == 0:
             self.job = job
             self.sim.activate(job, job.activate_job())

simso/core/__init__.py

@@ -2,10 +2,10 @@
 The core module include all the classes needed for the simulation.
 """
 
+from simso.core.Scheduler import Scheduler
 from simso.core.JobEvent import JobEvent
 from simso.core.ProcEvent import ProcEvent
 from simso.core.Model import Model
 from simso.core.Processor import Processor
-from simso.core.Scheduler import Scheduler
 from simso.core.Timer import Timer
 from simso.core.results import Results

simso/utils/probabilistic_calc.py

@@ -0,0 +1,48 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Nov 27 17:23:01 2018
+
+@author: sbenamor
+"""
+
+from random import random
+import numpy as np
+
+
+def random_int_from_distr(proba_dist, n_sample=1):
+    """ function that generate n random value according to a given
+        discrete probability distribution proba_dist
+
+    Args:
+        - proba_dist (numpy array 2*m): discrete probability distribution with m possible value.
+        - n_sample (int): number of generated samples.
+
+    Returns:
+        - list: list of n random generated values.
+
+    Example:
+        >>> randon_int_distr(np.array([[5],[1]]),1) #doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
+        [5]
+        >>> randon_int_distr(np.array([[2,3,8],[.1, .2, .7]]),1)[0] in [2,3,8]  #doctest: \
+        +ELLIPSIS +NORMALIZE_WHITESPACE
+        1
+        >>> np.all(np.isin(randon_int_distr(np.array([[2,3,8],[.1, .2, .7]]),5), [2,3,8]))  \
+        #doctest: +ELLIPSIS +NORMALIZE_WHITESPACE
+        True
+    """
+    samples = []
+
+    cdf = np.cumsum(proba_dist[1, :])    # Cumulative Distribution Function
+
+    for _ in range(n_sample):
+        proba = random()          # generate a probability value uniformly between 0 and 1
+        rand_value_index = np.argmax(cdf > proba)    #  transform generated probability to a value from the distribution using cdf function
+        samples.append(int(proba_dist[0, rand_value_index]))
+
+    return samples
+
+
+if __name__ == "__main__":
+    import doctest
+    doctest.testmod()