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502 | ------------------------------------------------------------------------------
------------------------------------------------------------------------------
-- Cheddar is a GNU GPL real-time scheduling analysis tool.
-- This program provides services to automatically check schedulability and
-- other performance criteria of real-time architecture models.
--
-- Copyright (C) 2002-2023, Frank Singhoff, Alain Plantec, Jerome Legrand,
-- Hai Nam Tran, Stephane Rubini
--
-- The Cheddar project was started in 2002 by
-- Frank Singhoff, Lab-STICC UMR 6285, Université de Bretagne Occidentale
--
-- Cheddar has been published in the "Agence de Protection des Programmes/France" in 2008.
-- Since 2008, Ellidiss technologies also contributes to the development of
-- Cheddar and provides industrial support.
--
-- The full list of contributors and sponsors can be found in README.md
--
-- This program is free software; you can redistribute it and/or modify
-- it under the terms of the GNU General Public License as published by
-- the Free Software Foundation; either version 2 of the License, or
-- (at your option) any later version.
--
-- This program is distributed in the hope that it will be useful,
-- but WITHOUT ANY WARRANTY; without even the implied warranty of
-- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-- GNU General Public License for more details.
--
-- You should have received a copy of the GNU General Public License
-- along with this program; if not, write to the Free Software
-- Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
--
--
-- Contact : cheddar@listes.univ-brest.fr
--
------------------------------------------------------------------------------
-- Last update :
-- $Rev: 4589 $
-- $Date: 2023-09-29 16:02:19 +0200 (ven., 29 sept. 2023) $
-- $Author: singhoff $
------------------------------------------------------------------------------
------------------------------------------------------------------------------
with Ada.text_IO; use Ada.text_IO;
with Ada.Integer_text_IO; use Ada.Integer_text_IO;
with Ada.Float_Text_IO; use Ada.Float_Text_IO;
with Ada.Numerics.Elementary_Functions;
use Ada.Numerics.Elementary_Functions;
with Ada.Strings; use Ada.Strings;
with Ada.Strings.Fixed; use Ada.Strings.Fixed;
with Ada.Numerics.Float_Random ; use Ada.Numerics.Float_Random ;
with unbounded_strings; use unbounded_strings;
with Tasks; use Tasks;
with Task_Set; use Task_Set;
with Resources; use Resources;
with Resource_Set; use Resource_Set;
with Ada.Strings.Unbounded; use Ada.Strings.Unbounded;
with Unbounded_Strings; use Unbounded_Strings;
with convert_unbounded_strings;
use unbounded_strings.unbounded_string_list_package;
with feasibility_test.feasibility_interval; use feasibility_test.feasibility_interval;
with Core_Units; use Core_Units;
use Core_Units.Core_Units_Table_Package;
--with Processors.extended; use Processors.extended;
with Scheduler_Interface; use Scheduler_Interface;
with Address_Spaces; use Address_Spaces;
with Address_Space_Set; use Address_Space_Set;
with Processors; use Processors;
with Processor_Set; use Processor_Set;
with processor_interface; use processor_interface;
with Call_Framework; use Call_Framework;
with Call_Framework_Interface; use Call_Framework_Interface;
use Call_Framework_Interface.Framework_Response_Package;
use Call_Framework_Interface.Framework_Request_Package;
with Call_Scheduling_Framework; use Call_Scheduling_Framework;
with Pipe_Commands; use Pipe_Commands;
with Ada.Text_IO; use Ada.Text_IO;
with Ada.Strings.Unbounded; use Ada.Strings.Unbounded;
with Ada.Text_IO.Unbounded_IO; use Ada.Text_IO.Unbounded_IO;
with Ada.Directories; use Ada.Directories;
with GNAT.OS_Lib; use GNAT.OS_Lib;
with Debug; use Debug;
package body Paes_For_Clustering is
-------------------------
-- init_for_clustering --
-------------------------
procedure init_for_clustering
is
begin
-- initialise the current solution c with values from 1 to genes
-- as we suppose each function is assigned to a task.
--
for i in 1..genes loop
c.chrom(i) := i;
end loop;
-- Initialize the Cheddar framework
--
Call_Framework.initialize (False);
Create_system (Initial_System);
-- Initialize the list of all possible fitness functions
--
for i in 1 .. MAX_FITNESS loop
FitnessFunctions(i).Is_selected := 0;
end loop;
FitnessFunctions(1).Name := To_Unbounded_String("f1 = preemptions"); -- To Min
FitnessFunctions(2).Name := To_Unbounded_String("f2 = contextSwitches"); -- To Min
FitnessFunctions(3).Name := To_Unbounded_String("f3 = tasks"); -- To Min
FitnessFunctions(4).Name := To_Unbounded_String("f4 = sum(Li) = sum(Di-Ri)");-- To Max --
FitnessFunctions(5).Name := To_Unbounded_String("f5 = sum(Ri/Di)"); -- To Min
FitnessFunctions(6).Name := To_Unbounded_String("f6 = min(Li)"); -- To Max --
FitnessFunctions(7).Name := To_Unbounded_String("f7 = sum(Ri)"); -- To Min
FitnessFunctions(8).Name := To_Unbounded_String("f8 = max(Ri)"); -- To Min
FitnessFunctions(9).Name := To_Unbounded_String("f9 = sum(Bi)"); -- To Min
FitnessFunctions(10).Name := To_Unbounded_String("f10 = max(Bi)"); -- To Min
FitnessFunctions(11).Name := To_Unbounded_String("f11 = sharedResources"); -- To Min
-- Initialise the float generator
--reset(G);
end init_for_clustering;
-----------------------------
-- evaluate_for_clustering --
-----------------------------
procedure evaluate_for_clustering (s : in out solution; eidx : in Natural) is
F : Ada.Text_IO.File_Type;
line : unbounded_String;
Buffer : unbounded_String;
j : integer;
begin
j := 0;
for i in 1 .. MAX_FITNESS loop
if FitnessFunctions(i).Is_selected = 1 then
j := j + 1;
-- open the file output_eidx.txt
-- then read the line corresponding to the selected FitnessFunction
Open (File => F,
Mode => Ada.Text_IO.In_File,
Name => "Output" & eidx'img & ".txt");
Ada.Text_IO.Set_Line (File => F, To => Ada.Text_IO.Count(i+1));
line := To_unbounded_string(Get_Line (File => F));
-- We distinguish the fitness to maximize i.e. (f4 and f6)
-- in order to make all abjectives for minimization
-- So, we transforme f4 and f6 as follow :
-- f4 = Hyperperiod_of_Initial_Taskset - f4
-- f6 = Hyperperiod_of_Initial_Taskset - f6
If (i = 4) or (i = 6) then
s.obj(j) := float(Hyperperiod_of_Initial_Taskset) -
Float'Value(To_String(Unbounded_Slice(line,
length(FitnessFunctions(i).Name & " = "),
length(line))));
else
s.obj(j) := Float'Value(To_String(Unbounded_Slice(line,
length(FitnessFunctions(i).Name & " = "),
length(line))));
end if;
close(File => F);
end if;
end loop;
--Deleting the file "Output eidx.txt"
--
Open (File => F,
Mode => Ada.Text_IO.In_File,
Name => "Output" & eidx'img & ".txt");
Ada.text_IO.Delete(File => F);
end evaluate_for_clustering;
---------------------------
-- Mutate_for_clustering --
---------------------------
procedure mutate_for_clustering (s : in out solution; eidx : in Natural) is
random_task, fn : integer;
A_system : System;
A_Task_set, New_Task_set : Tasks_Set;
Nb_tasks, New_nb_tasks : integer;
period_fn, period_j : natural;
harmonic_tasks : chrom_type;
tmp_mod, k, j, counter : integer;
is_harmonic, exist : boolean;
Sol_is_mutated : boolean;
A_sol : solution;
Nb_harmonic_tasks : integer;
FileStream : stream;
command : unbounded_String;
F : Ada.Text_IO.File_Type;
line : unbounded_String;
Buffer : unbounded_String;
G : Ada.Numerics.Float_Random.Generator;
New_resource_set : Resources_Set;
begin
Create_system (A_system);
sol_is_mutated := false;
reset(G); -- Initialise the float generator
-- I think, we should add a counter, if this counter reach a threashold
-- and it failed to generate a mutated solution then we stop
counter := 1;
while (not sol_is_mutated) and (counter <= 100000) loop
Put_Debug ("................................................................");
Put_Debug ("The " & counter'img & " attempt of the mutation procedure ");
Put_Debug ("................................................................");
A_sol := s;
Appling_clustering_rules (A_system, A_sol);
Nb_tasks := Number_of_tasks (A_sol);
fn := 0;
-- choose randomly an index of a function between 1 and genes
while (fn > genes) or (fn < 1) loop
fn := integer (float(genes) * random(G));
end loop;
Put_Debug ("The randomly chosen function is : " & fn'img);
-- determine the set of harmonic tasks with the choosen function fn
K := 0;
period_fn := Get (My_Tasks => Initial_system.Tasks,
Task_Name => Suppress_Space (To_Unbounded_String ("Task" & fn'Img)),
Param_Name => Period);
for j in 1 .. Nb_tasks loop
period_j := Get (My_Tasks => A_system.Tasks,
Task_Name => Suppress_Space (To_Unbounded_String ("Task" & j'Img)),
Param_Name => Period);
if period_fn > period_j then
tmp_mod := period_fn mod period_j;
else
tmp_mod := period_j mod period_fn;
end if;
if tmp_mod = 0 then
Put_Debug ("period_fn = " & period_fn'Img & " period_j = " & period_j'Img);
k := k + 1;
harmonic_tasks (k) := j;
Put_Debug ("harmonic_tasks (" & k'Img & ") = " & j'Img);
end if;
end loop;
nb_harmonic_tasks := k;
-- if the set of tasks which are harmonic with "fn" is not empty
-- else i.e the function fn is not harmonic with any task, only its own task
-- then we repeat the procedure with another function chosen randomly
if nb_harmonic_tasks /= 0 then
-- choose randomly a task random_task over tasks in the set harmonic_tasks
-- (including tau_j = chrom[fn]);
is_harmonic := false;
while (not is_harmonic) loop
random_task := 0;
-- generate a random number of task comprised between 1 and nb_tasks
while (random_task > nb_tasks) or (random_task < 1) loop
random_task := integer (float(nb_tasks) * random(G));
end loop;
Put_Debug ("nb_tasks =" & nb_tasks'img & " and The task chosen randomly is :" & random_task'img);
Put_Debug ("The harmonic tasks with " & fn'Img & " are: ");
for j in 1 .. nb_harmonic_tasks loop
Put_Debug (" " & harmonic_tasks (j)'Img);
end loop;
Put_Debug(" ");
-- verify if random_task is among the set of harmonic tasks
j := 1;
exist := false;
while (not exist) and (j <= nb_harmonic_tasks) loop
if random_task = harmonic_tasks (j) then
exist := true;
end if;
j := j + 1;
end loop;
if exist then
is_harmonic := true;
end if;
end loop;
if (random_task /= A_sol.chrom(fn)) then -- if the function "fn" is not intially in
-- the task "random_task" the "fn" is moved
-- to the task "random_task"
A_sol.chrom(fn) := random_task;
sol_is_mutated := true;
elsif (not is_isolated (fn, A_sol)) then
-- if coincidentally the function "fn" is intially in the task "random_task"
-- then if the function "fn" is not initially isolated, we create a new task
-- in which we isolate it
-- else i.e the function "fn" is alone then we repeat the procedure with another function
-- chosen randomly
A_sol.chrom(fn) := nb_tasks + 1;
sol_is_mutated := true;
end if;
end if;
if sol_is_mutated then
Put_Debug(" ");-
Put_Debug ("The mutated solution is : ");
print_debug_genome(A_sol);
Put_Debug(" ");
-- normalize the mutate solution
normalize(A_sol);
Put_Debug(" ");
Put_Debug ("After normalization the candidate solution is : ");
print_debug_genome(A_sol);
Put_Debug(" ");
----------------------------------------------------------------------------------------
-- After generating a mutate solution, we shoud verify :
-- 1) If the new solution is consistent or not i.e two non-harmonic functions
-- which are grouped alone in the same task.
-- 2) If it was a consistent solution then we should verify its schedulability
-- by calling the Cheddar tool to simulate the scheduling of the candidate task set
-- Else, we must regenerate a new candidate solution
-----------------------------------------------------------------------------------------
If Check_Consistency_Of_A_Solution (A_sol) then
Put_Debug (" The candidate solution is consistent and then we check the schedulability");
-- check the schedulability
Appling_clustering_rules (A_System, A_sol);
New_nb_tasks := Number_of_tasks (A_sol);
-- Laurent //
command := To_Unbounded_String("candidate_solution" & eidx'Img & ".xmlv3");
Write_To_Xml_File(A_System => A_System,
File_Name => To_String(command));
command := To_Unbounded_String("~/call_cheddar "
& Hyperperiod_of_Initial_Taskset'img
& " candidate_solution\" & eidx'Img & ".xmlv3");
FileStream := execute(To_string(command), read_file);
loop
begin
Buffer := read_next(FileStream);
exception
when Pipe_Commands.End_of_file =>
exit;
end;
end loop;
close(FileStream);
Open(F, Ada.Text_IO.In_File,"Output" & eidx'Img & ".txt");
line := To_Unbounded_String(get_line(F));
if line = "schedulability : true" then
Put_Debug("**The candidate task set is schedulable**");
sol_is_mutated := true;
s := A_sol;
else
Put_Debug("**The candidate task set is NOT schedulable**");
sol_is_mutated := false;
counter := counter + 1;
end if;
Close(F);
else
Put_Debug (" The candidate solution is NOt consistent and then " &
" we should regenerate another candidate solution");
sol_is_mutated := false;
counter := counter + 1;
end if;
end if;
end loop;
if counter > 100000 then
Put_Debug(" ");--New_Line;
Put_Debug(" ");--New_Line;
Put_Debug("Exit the program, there is no schedulable candidate solution !");
Put_Debug(" ");--New_Line;
Put_Debug(" ");--New_Line;
OS_Exit (0);
end if;
end mutate_for_clustering;
-----------------
-- is_isolated --
-----------------
function is_isolated(t : integer; s : solution) return boolean
is
result : boolean := true;
i : integer := 1;
begin
while (result and i <= genes) loop
if (s.chrom(i) = s.chrom(t)) and then (t /= i) then
result := false;
end if;
i := i + 1;
end loop;
return result;
end is_isolated;
---------------
-- Normalize --
---------------
procedure normalize(s : in out solution)
is
nb_tasks : integer := 1;
-- the vector var is used to know if a gene is normalized or not yet
var : chrom_Type;
begin
-- initialization of the vector var.
for i in 1..genes loop
var(i) := 0;
end loop;
------------------------------------------------------------
-- if var(i) = 0 ==> s.chrom(i) is not yet normalized
-- if var(i) = 1 ==> s.chrom(i) is normalized
------------------------------------------------------------
for i in 1..genes loop
if (var(i) = 0) then
for j in i+1..genes loop
if (s.chrom(j) = s.chrom(i)) and then (var(j) = 0) then
var(j) := 1;
-- if s.chrom(i) is not normalized then all s.chrom(j) (which egal s.all.chrom(i))
-- are not normalized
if (s.chrom(i) /= nb_tasks) then
s.chrom(j) := nb_tasks;
end if;
end if;
end loop;
-- we normalize s.chrom(i)
if (s.chrom(i) /= nb_tasks) then
s.chrom(i) := nb_tasks;
end if;
var(i) := 1;
nb_tasks := nb_tasks + 1;
end if;
end loop;
end normalize;
end Paes_For_Clustering;
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