* \f$\sum_if(x_i)\f$, where \f$f\f$ is a strictly increasing concave
* function.
*
+ *
* Constraint:
* - bound (set)
* - shared (set)
* This is usefull for the sharing of resources for various models.
* For instance, for the network model, each link is associated
* to a constraint and each communication to a variable.
+ *
+ *
+ * Implementation details
+ *
+ * For implementation reasons, we are interested in distinguishing variables that actually participate to the computation of constraints, and those who are part of the equations but are stuck to zero.
+ * We call enabled variables, those which var.weight is strictly positive. Zero-weight variables are called disabled variables.
+ * Unfortunately this concept of enabled/disabled variables intersects with active/inactive variable.
+ * Semantically, the intent is similar, but the conditions under which a variable is active is slightly more strict than the conditions for it to be enabled.
+ * A variable is active only if its var.value is non-zero (and, by construction, its var.weight is non-zero).
+ * In general, variables remain disabled after their creation, which often models an initialization phase (e.g. first packet propagating in the network). Then, it is enabled by the corresponding model. Afterwards, the max-min solver (lmm_solve()) activates it when appropriate. It is possible that the variable is again disabled, e.g. to model the pausing of an action.
+ *
+ *
+ * Concurrency limit and maximum
*
+ * We call concurrency, the number of variables that can be enabled at any time for each constraint.
+ * From a model perspective, this "concurrency" often represents the number of actions that actually compete for one constraint.
+ * The LMM solver is able to limit the concurrency for each constraint, and to monitor its maximum value.
+ *
+ * One may want to limit the concurrency of constraints for essentially three reasons:
+ * - Keep LMM system in a size that can be solved (it does not react very well with tens of thousands of variables per constraint)
+ * - Stay within parameters where the fluid model is accurate enough.
+ * - Model serialization effects
+ *
+ * The concurrency limit can also be set to a negative value to disable concurrency limit. This can improve performance slightly.
+ *
+ * Overall, each constraint contains three fields related to concurrency:
+ * - concurrency_limit which is the limit enforced by the solver
+ * - concurrency_current which is the current concurrency
+ * - concurrency_maximum which is the observed maximum concurrency
+ *
+ * Variables also have one field related to concurrency: concurrency_share.
+ * In effect, in some cases, one variable is involved multiple times (i.e. two elements) in a constraint.
+ * For example, cross-traffic is modeled using 2 elements per constraint.
+ * concurrency_share formally corresponds to the maximum number of elements that associate the variable and any given constraint.
*/
XBT_PUBLIC_DATA(double) sg_maxmin_precision;
* @param cnst The constraint to share
* @return 1 if shared, 0 otherwise
*/
-XBT_PUBLIC(int) lmm_constraint_is_shared(lmm_constraint_t cnst);
+XBT_PUBLIC(int) lmm_constraint_sharing_policy(lmm_constraint_t cnst);
/**
* @brief Free a constraint
*/
XBT_PUBLIC(double) lmm_constraint_get_usage(lmm_constraint_t cnst);
+/**
+ * @brief Sets the concurrency limit for this constraint
+ *
+ * @param cnst A constraint
+ * @param concurrency_limit The concurrency limit to use for this constraint
+ */
+XBT_PUBLIC(void) lmm_constraint_concurrency_limit_set(lmm_constraint_t cnst, int concurrency_limit);
+
+/**
+ * @brief Gets the concurrency limit for this constraint
+ *
+ * @param cnst A constraint
+ * @return The concurrency limit used by this constraint
+ */
+XBT_PUBLIC(int) lmm_constraint_concurrency_limit_get(lmm_constraint_t cnst);
+
+
+/**
+ * @brief Reset the concurrency maximum for a given variable (we will update the maximum to reflect constraint evolution).
+ *
+ * @param cnst A constraint
+ *
+*/
+XBT_PUBLIC(void) lmm_constraint_concurrency_maximum_reset(lmm_constraint_t cnst);
+
+
+/**
+ * @brief Get the concurrency maximum for a given variable (which reflects constraint evolution).
+ *
+ * @param cnst A constraint
+ * @return the maximum concurrency of the constraint
+ */
+XBT_PUBLIC(int) lmm_constraint_concurrency_maximum_get(lmm_constraint_t cnst);
+
+
/**
* @brief Create a new Linear MaxMin variable
*
*/
XBT_PUBLIC(double) lmm_variable_getbound(lmm_variable_t var);
+/**
+ * @brief Set the concurrent share of the variable
+ *
+ * @param var A variable
+ * @param concurrency_share The new concurrency share
+ */
+XBT_PUBLIC(void) lmm_variable_concurrency_share_set(lmm_variable_t var, short int concurrency_share);
+
/**
* @brief Remove a variable from a constraint
*
*/
XBT_PUBLIC(int) lmm_constraint_used(lmm_system_t sys, lmm_constraint_t cnst);
+/**
+ * @brief Print the lmm system
+ *
+ * @param sys The lmm system to print
+ */
+XBT_PUBLIC(void) lmm_print(lmm_system_t sys);
+
/**
* @brief Solve the lmm system
*
