X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/a8e926e86ef601549e7f37b4b2b1d210dc6dd5f1..d3d060aead49b9969ac0e9cb83d58b7959925460:/src/surf/lagrange.c?ds=sidebyside

diff --git a/src/surf/lagrange.c b/src/surf/lagrange.c
index c6ad3d8f35..7cf03324c6 100644
--- a/src/surf/lagrange.c
+++ b/src/surf/lagrange.c
@@ -1,10 +1,7 @@
 /* 	$Id$	 */
-
 /* Copyright (c) 2007 Arnaud Legrand, Pedro Velho. All rights reserved.     */
-
 /* This program is free software; you can redistribute it and/or modify it
  * under the terms of the license (GNU LGPL) which comes with this package. */
-
 /*
  * Modelling the proportional fairness using the Lagrange Optimization 
  * Approach. For a detailed description see:
@@ -21,125 +18,354 @@
 #endif
 
 
-XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf,
-				"Logging specific to SURF (lagrange)");
+XBT_LOG_NEW_DEFAULT_SUBCATEGORY(surf_lagrange, surf, "Logging specific to SURF (lagrange)");
+
+/*
+ * Local prototypes to implement the lagrangian optimization with optimal step, also called dicotomi.
+ */
+//solves the proportional fairness using a lagrange optimizition with dicotomi step
+void   lagrange_solve       (lmm_system_t sys);
+//computes the value of the dicotomi using a initial values, init, with a specific variable or constraint
+double dicotomi(double init, double diff(double, void*), void *var_cnst, double min_error);
+//computes the value of the differential of variable param_var applied to mu  
+double partial_diff_mu      (double mu, void * param_var);
+//computes the value of the differential of constraint param_cnst applied to lambda  
+double partial_diff_lambda  (double lambda, void * param_cnst);
+
 
 void lagrange_solve(lmm_system_t sys)
 {
-
   /*
    * Lagrange Variables.
    */
-  double epsilon_min_error = 1e-6;
+  int max_iterations= 10000;
+  double epsilon_min_error = 1e-4;
+  double dicotomi_min_error = 1e-8;
   double overall_error = 1;
-  double sigma_step = 0.5e-3;
-  double capacity_error, bound_error;
-  double sum_capacity = 0;
-  double sum_bound = 0;
-  
 
   /*
    * Variables to manipulate the data structure proposed to model the maxmin
    * fairness. See docummentation for more details.
    */
-  lmm_element_t elem = NULL;
-  xbt_swag_t cnst_list = NULL;
-  lmm_constraint_t cnst1 = NULL;
-  lmm_constraint_t cnst2 = NULL;
-  xbt_swag_t var_list = NULL;
-  xbt_swag_t elem_list = NULL;
-  lmm_variable_t var1 = NULL;
-  lmm_variable_t var2 = NULL;
+  xbt_swag_t elem_list  = NULL;
+  lmm_element_t elem    = NULL;
 
+  xbt_swag_t cnst_list  = NULL;
+  lmm_constraint_t cnst = NULL;
+  
+  xbt_swag_t var_list   = NULL;
+  lmm_variable_t var    = NULL;
 
   /*
    * Auxiliar variables.
    */
   int iteration=0;
-  int max_iterations=100000;
-  double mu_partial=0;
-  double lambda_partial=0;
+  double tmp=0;
+  int i;
+   
 
+  DEBUG0("Iterative method configuration snapshot =====>");
+  DEBUG1("#### Maximum number of iterations       : %d", max_iterations);
+  DEBUG1("#### Minimum error tolerated            : %e", epsilon_min_error);  
+  DEBUG1("#### Minimum error tolerated (dicotomi) : %e", dicotomi_min_error);
 
   if ( !(sys->modified))
     return;
-  
+
   /* 
    * Initialize the var list variable with only the active variables. 
-   * Associate an index in the swag variables and compute the sum
-   * of all round trip time constraints. May change depending on the 
-   * function f(x).
+   * Associate an index in the swag variables. Initialize mu.
    */
-  var_list = &(sys->active_variable_set);
+  var_list = &(sys->variable_set);
   i=0;
-  xbt_swag_foreach(var1, var_list) {
-    if(var1->weight != 0.0){
-      i++;
-      sum_bound += var1->bound;
+  xbt_swag_foreach(var, var_list) {    
+    if((var->bound > 0.0) || (var->weight <= 0.0)){
+      DEBUG1("#### NOTE var(%d) is a boundless variable", i);
+      var->mu = -1.0;
+    } else{ 
+      var->mu =   1.0;
+      var->new_mu = 2.0;
     }
+    DEBUG2("#### var(%d)->mu :  %e", i, var->mu);
+    DEBUG2("#### var(%d)->weight: %e", i, var->weight);
+    i++;
   }
 
   /* 
-   * Compute the sum of all capacities constraints. May change depending
-   * on the function f(x).
+   * Initialize lambda.
    */
   cnst_list=&(sys->active_constraint_set); 
-  xbt_swag_foreach(cnst1, cnst_list) {
-     sum_capacity += cnst1->value;
+  xbt_swag_foreach(cnst, cnst_list){
+    cnst->lambda = 1.0;
+    cnst->new_lambda = 2.0;
+    DEBUG2("#### cnst(%p)->lambda :  %e", cnst, cnst->lambda);
   }
-
   
   /*
    * While doesn't reach a minimun error or a number maximum of iterations.
    */
   while(overall_error > epsilon_min_error && iteration < max_iterations){
-
+   
     iteration++;
+    DEBUG1("************** ITERATION %d **************", iteration);    
 
-    
-    
-    /*                        d Dual
-     * Compute the value of ----------- (\lambda^k, \mu^k) this portion
-     *                       d \mu_i^k
-     * of code depends on function f(x).
+    /*                       
+     * Compute the value of mu_i
      */
-    bound_error = 0;
-    xbt_swag_foreach(var1, var_list) {
-      
-      mu_partial = 0;
-      
-      //for each link elem1 that uses flow of variable var1 do
-      //mu_partial += elem1->weight + var1->bound; 
-
-      mu_partial = - (1 / mu_partial) + sum_bound;
-
-      var1->bound = var1->bound + sigma_step * mu_partial;
+    //forall mu_i in mu_1, mu_2, ..., mu_n
+    xbt_swag_foreach(var, var_list) {
+      if((var->bound >= 0) && (var->weight > 0) ){
+	var->new_mu = dicotomi(var->mu, partial_diff_mu, var, dicotomi_min_error);
+	if(var->new_mu < 0) var->new_mu = 0;
+	var->mu = var->new_mu;
+      }
     }
 
-    
-    
     /*
-     * Verify for each capacity constraint (lambda) the error associated. 
+     * Compute the value of lambda_i
      */
-    xbt_swag_foreach(cnst1, cnst_list) {
-      cnst2 = xbt_swag_getNext(cnst1,(var_list)->offset);
-      if(cnst2 != NULL){
-	 capacity_error += fabs(cnst1->value - cnsts2->value);
-      }
+    //forall lambda_i in lambda_1, lambda_2, ..., lambda_n
+    xbt_swag_foreach(cnst, cnst_list) {
+      cnst->new_lambda = dicotomi(cnst->lambda, partial_diff_lambda, cnst, dicotomi_min_error);
+      DEBUG2("====> cnst->lambda (%p) = %e", cnst, cnst->new_lambda);      
+      cnst->lambda = cnst->new_lambda;
     }
 
+
+/*     /\*                        */
+/*      * Update values of mu and lambda */
+/*      *\/ */
+/*     //forall mu_i in mu_1, mu_2, ..., mu_n */
+/*     xbt_swag_foreach(var, var_list) { */
+/*       var->mu = var->new_mu ; */
+/*     } */
+  
+/*     //forall lambda_i in lambda_1, lambda_2, ..., lambda_n */
+/*     xbt_swag_foreach(cnst, cnst_list) { */
+/*       cnst->lambda = cnst->new_lambda; */
+/*     } */
+
     /*
-     * Verify for each variable the error of round trip time constraint (mu).
+     * Now computes the values of each variable (\rho) based on
+     * the values of \lambda and \mu.
      */
-    bound_error = 0;
-    xbt_swag_foreach(var1, var_list) {
-      var2 = xbt_swag_getNext(var1,(var_list)->offset);
-      if(var2 != NULL){
-	bound_error += fabs( var2->weight - var1->weight);
+    overall_error=0;   
+    xbt_swag_foreach(var, var_list) {
+      if(var->weight <=0) 
+	var->value = 0.0;
+      else {
+	tmp = 0;
+	for(i=0; i<var->cnsts_number; i++){
+	  tmp += (var->cnsts[i].constraint)->lambda;
+	  if(var->bound > 0) 
+	    tmp+=var->mu;
+	}
+
+	if(tmp == 0.0)
+	  WARN0("CAUTION: division by 0.0");
+
+	//computes de overall_error
+	if(overall_error < fabs(var->value - 1.0/tmp)){
+	  overall_error = fabs(var->value - 1.0/tmp);
+	}
+	var->value = 1.0 / tmp;
       }
+      DEBUG4("======> value of var %s (%p)  = %e, overall_error = %e", (char *)var->id, var, var->value, overall_error);       
     }
+  }
 
-    overall_error = capacity_error + bound_error;
+
+  //verify the KKT property for each link
+  xbt_swag_foreach(cnst, cnst_list){
+    tmp = 0;
+    elem_list = &(cnst->element_set);
+    xbt_swag_foreach(elem, elem_list) {
+      var = elem->variable;
+      if(var->weight<=0) continue;
+      tmp += var->value;
+    }
+  
+    tmp = tmp - cnst->bound;
+
+    if(tmp > epsilon_min_error){
+      WARN4("The link %s(%p) doesn't match the KKT property, expected less than %e and got %e", (char *)cnst->id, cnst, epsilon_min_error, tmp);
+    }
+  
   }
+  
+  //verify the KKT property of each flow
+  xbt_swag_foreach(var, var_list){
+    if(var->bound <= 0 || var->weight <= 0) continue;
+    tmp = 0;
+    tmp = (var->value - var->bound);
 
+    
+    if(tmp != 0 ||  var->mu != 0){
+      WARN4("The flow %s(%p) doesn't match the KKT property, value expected (=0) got (lambda=%e) (sum_rho=%e)", (char *)var->id, var, var->mu, tmp);
+    }
+
+  }
+
+  if(overall_error <= epsilon_min_error){
+    DEBUG1("The method converge in %d iterations.", iteration);
+  }else{
+    WARN1("Method reach %d iterations, which is the maxmimun number of iterations allowed.", iteration);
+  }
 }
+
+/*
+ * Returns a double value corresponding to the result of a dicotomi proccess with
+ * respect to a given variable/constraint (\mu in the case of a variable or \lambda in
+ * case of a constraint) and a initial value init. 
+ *
+ * @param init initial value for \mu or \lambda
+ * @param diff a function that computes the differential of with respect a \mu or \lambda
+ * @param var_cnst a pointer to a variable or constraint 
+ * @param min_erro a minimun error tolerated
+ *
+ * @return a double correponding to the result of the dicotomial process
+ */
+double dicotomi(double init, double diff(double, void*), void *var_cnst, double min_error){
+  double min, max;
+  double overall_error;
+  double middle;
+  double min_diff, max_diff, middle_diff;
+  
+  min = max = init;
+
+  if(init == 0){
+    min = max = 1;
+  }
+
+  min_diff = max_diff = middle_diff = 0.0;
+  overall_error = 1;
+
+  if(diff(0.0, var_cnst) > 0){
+    DEBUG1("====> returning 0.0 (diff = %e)", diff(0.0, var_cnst));
+    return 0.0;
+  }
+
+  DEBUG0("====> not detected positive diff in 0");
+
+  while(overall_error > min_error){
+
+    min_diff = diff(min, var_cnst);
+    max_diff = diff(max, var_cnst);
+
+    DEBUG2("DICOTOMI ===> min = %e , max = %e", min, max);
+    DEBUG2("DICOTOMI ===> diffmin = %e , diffmax = %e", min_diff, max_diff);
+
+    if( min_diff > 0 && max_diff > 0 ){
+      if(min == max){
+	min = min / 2.0;
+      }else{
+	max = min;
+      }
+    }else if( min_diff < 0 && max_diff < 0 ){
+      if(min == max){
+	max = max * 2.0;
+      }else{
+	min = max;
+      }
+    }else if( min_diff < 0 && max_diff > 0 ){
+      middle = (max + min)/2.0;
+      middle_diff = diff(middle, var_cnst);
+      overall_error = fabs(min - max);
+
+      if( middle_diff < 0 ){
+	min = middle;
+      }else if( middle_diff > 0 ){
+	max = middle;
+      }else{
+	WARN0("Found an optimal solution with 0 error!");
+	overall_error = 0;
+	return middle;
+      }
+
+    }else if(min_diff == 0){
+      return min;
+    }else if(max_diff == 0){
+      return max;
+    }else if(min_diff > 0 && max_diff < 0){
+      WARN0("The impossible happened, partial_diff(min) > 0 && partial_diff(max) < 0");
+    }
+  }
+
+
+  DEBUG1("====> returning %e", (min+max)/2.0);
+  return ((min+max)/2.0);
+}
+
+/*
+ *
+ */
+double partial_diff_mu(double mu, void *param_var){
+  double mu_partial=0.0;
+  lmm_variable_t var = (lmm_variable_t)param_var;
+  int i;
+
+  //for each link with capacity cnsts[i] that uses flow of variable var do
+  for(i=0; i<var->cnsts_number; i++)
+    mu_partial += (var->cnsts[i].constraint)->lambda + mu;
+  
+  mu_partial = (-1.0/mu_partial) + var->bound;
+
+  return mu_partial;
+}
+
+/*
+ *
+ */
+double partial_diff_lambda(double lambda, void *param_cnst){
+
+  double tmp=0.0;
+  int i;
+  xbt_swag_t elem_list = NULL;
+  lmm_element_t elem = NULL;
+  lmm_variable_t var = NULL;
+  lmm_constraint_t cnst= (lmm_constraint_t) param_cnst;
+  double lambda_partial=0.0;
+
+
+  elem_list = &(cnst->element_set);
+
+
+  DEBUG2("Computting diff of cnst (%p) %s", cnst, (char *)cnst->id);
+  
+  xbt_swag_foreach(elem, elem_list) {
+    var = elem->variable;
+    if(var->weight<=0) continue;
+    
+    tmp = 0;
+
+    //DEBUG2("===> Variable (%p) %s", var, (char *)var->id);
+
+    for(i=0; i<var->cnsts_number; i++){
+      tmp += (var->cnsts[i].constraint)->lambda;
+      //DEBUG1("======> lambda %e + ", (var->cnsts[i].constraint)->lambda);
+    }
+	
+    if(var->bound > 0)
+      tmp += var->mu;
+    
+
+    //DEBUG2("======> lambda - %e + %e ", cnst->lambda, lambda);
+
+    tmp = tmp - cnst->lambda + lambda;
+    
+    //avoid a disaster value of lambda
+    //if(tmp==0) tmp = 10e-8;
+    
+    lambda_partial += (-1.0/tmp);
+
+    //DEBUG1("======> %e ", (-1.0/tmp));
+  }
+
+  lambda_partial += cnst->bound;
+
+  //DEBUG1("===> %e ", lambda_partial);
+
+  return lambda_partial;
+}
+  
+