X-Git-Url: http://info.iut-bm.univ-fcomte.fr/pub/gitweb/simgrid.git/blobdiff_plain/e530b77c44cac0b95410af2c84132bf13fdb474b..554542681a91f6e2f03abc8e08cba77f487f993d:/src/surf/lagrange.c diff --git a/src/surf/lagrange.c b/src/surf/lagrange.c index 786a4c9a31..8190dfba33 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: @@ -23,7 +20,6 @@ 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. */ @@ -35,7 +31,8 @@ double dicotomi(double init, double diff(double, void*), void *var_cnst, double 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); - +//auxiliar function to compute the partial_diff +double diff_aux(lmm_variable_t var, double x); void lagrange_solve(lmm_system_t sys) @@ -43,12 +40,11 @@ void lagrange_solve(lmm_system_t sys) /* * Lagrange Variables. */ - int max_iterations= 100; - double epsilon_min_error = 1e-4; + int max_iterations= 10000; + double epsilon_min_error = 1e-4; double dicotomi_min_error = 1e-8; double overall_error = 1; - /* * Variables to manipulate the data structure proposed to model the maxmin * fairness. See docummentation for more details. @@ -56,14 +52,12 @@ void lagrange_solve(lmm_system_t sys) 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. */ @@ -77,7 +71,6 @@ void lagrange_solve(lmm_system_t sys) DEBUG1("#### Minimum error tolerated : %e", epsilon_min_error); DEBUG1("#### Minimum error tolerated (dicotomi) : %e", dicotomi_min_error); - if ( !(sys->modified)) return; @@ -87,23 +80,24 @@ void lagrange_solve(lmm_system_t sys) */ var_list = &(sys->variable_set); i=0; - 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++; + 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++; } /* * Initialize lambda. */ cnst_list=&(sys->active_constraint_set); - xbt_swag_foreach(cnst, cnst_list) { + xbt_swag_foreach(cnst, cnst_list){ cnst->lambda = 1.0; cnst->new_lambda = 2.0; DEBUG2("#### cnst(%p)->lambda : %e", cnst, cnst->lambda); @@ -117,7 +111,6 @@ void lagrange_solve(lmm_system_t sys) iteration++; DEBUG1("************** ITERATION %d **************", iteration); - /* * Compute the value of mu_i */ @@ -126,6 +119,7 @@ void lagrange_solve(lmm_system_t sys) 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; } } @@ -135,24 +129,10 @@ void lagrange_solve(lmm_system_t sys) //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); - if(cnst->new_lambda < 0) cnst->new_lambda = 0; - } - - - /* - * 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) { + DEBUG2("====> cnst->lambda (%p) = %e", cnst, cnst->new_lambda); cnst->lambda = cnst->new_lambda; } - /* * Now computes the values of each variable (\rho) based on * the values of \lambda and \mu. @@ -162,17 +142,23 @@ void lagrange_solve(lmm_system_t sys) if(var->weight <=0) var->value = 0.0; else { + //compute sigma_i + mu_i tmp = 0; for(i=0; icnsts_number; i++){ tmp += (var->cnsts[i].constraint)->lambda; if(var->bound > 0) tmp+=var->mu; } - //computes de overall_error - if(overall_error < fabs(var->value - 1.0/tmp)){ - overall_error = fabs(var->value - 1.0/tmp); + + //uses the partial differential inverse function + tmp = var->func_fpi(var, tmp); + + //computes de overall_error using normalized value + if(overall_error < (fabs(var->value - tmp)/tmp) ){ + overall_error = (fabs(var->value - tmp)/tmp); } - var->value = 1.0 / tmp; + + var->value = tmp; } DEBUG4("======> value of var %s (%p) = %e, overall_error = %e", (char *)var->id, var, var->value, overall_error); } @@ -196,7 +182,6 @@ void lagrange_solve(lmm_system_t sys) } } - //verify the KKT property of each flow xbt_swag_foreach(var, var_list){ @@ -211,7 +196,6 @@ void lagrange_solve(lmm_system_t sys) } - if(overall_error <= epsilon_min_error){ DEBUG1("The method converge in %d iterations.", iteration); }else{ @@ -235,97 +219,165 @@ double dicotomi(double init, double diff(double, void*), void *var_cnst, double 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; - //DEBUG0("STARTING DICOTOMI... Debugging, format used [min, max], [D(min),D(max)]"); + 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){ - //DEBUG4("====> [%e, %e] , [%e,%e]", min, max, diff(min, var_cnst), diff(max, var_cnst)); - if( diff(min, var_cnst) > 0 && diff(max, var_cnst) > 0 ){ + 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( diff(min, var_cnst) < 0 && diff(max, var_cnst) < 0 ){ + }else if( min_diff < 0 && max_diff < 0 ){ if(min == max){ max = max * 2.0; }else{ min = max; } - }else if( diff(min, var_cnst) < 0 && diff(max, var_cnst) > 0 ){ + }else if( min_diff < 0 && max_diff > 0 ){ middle = (max + min)/2.0; - - if( diff(middle, var_cnst) < 0 ){ + middle_diff = diff(middle, var_cnst); + overall_error = fabs(min - max); + + if( middle_diff < 0 ){ min = middle; - }else if( diff(middle, var_cnst) > 0 ){ + }else if( middle_diff > 0 ){ max = middle; }else{ WARN0("Found an optimal solution with 0 error!"); overall_error = 0; + return middle; } - overall_error = fabs(min - max); - }else{ - WARN0("The impossible happened, partial_diff(min) >0 && partial_diff(max) < 0"); + + }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; + double sigma_mu=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 + //compute sigma_i for(i=0; icnsts_number; i++) - mu_partial += (var->cnsts[i].constraint)->lambda + mu; + sigma_mu += (var->cnsts[i].constraint)->lambda; + + //compute sigma_i + mu_i + sigma_mu += var->mu; - mu_partial = (-1.0/mu_partial) + var->bound; + //use auxiliar function passing (sigma_i + mu_i) + mu_partial = diff_aux(var, sigma_mu) ; + + //add the RTT limit + 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; - + double sigma_mu=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; + //initilize de sumation variable + sigma_mu = 0.0; + + //compute sigma_i of variable var for(i=0; icnsts_number; i++){ - tmp += (var->cnsts[i].constraint)->lambda; + sigma_mu += (var->cnsts[i].constraint)->lambda; } - if(var->bound > 0) - tmp += var->mu; - - tmp = tmp - cnst->lambda + lambda; - - //avoid a disaster value of lambda - if(tmp==0) lambda_partial = 10e-8; + //add mu_i if this flow has a RTT constraint associated + if(var->bound > 0) sigma_mu += var->mu; + + //replace value of cnst->lambda by the value of parameter lambda + sigma_mu = (sigma_mu - cnst->lambda) + lambda; - lambda_partial += (-1.0 /tmp); + //use the auxiliar function passing (\sigma_i + \mu_i) + lambda_partial += diff_aux(var, sigma_mu); } lambda_partial += cnst->bound; return lambda_partial; } + + +double diff_aux(lmm_variable_t var, double x){ + double tmp_fp, tmp_fpi, tmp_fpip, result; + + xbt_assert0(var->func_fp, "Initialize the protocol functions first create variables before."); + + tmp_fp = var->func_fp(var, x); + tmp_fpi = var->func_fpi(var, x); + tmp_fpip = var->func_fpip(var, x); + + result = tmp_fpip*(var->func_fp(var, tmp_fpi)); + result = result - tmp_fpi; + + result = result - (tmp_fpip * x); + + return result; +} + + + + + + + +