Package jline.api.mdd

Class Mdd_mcd

java.lang.Object
jline.api.mdd.Mdd_mcd
public class Mdd_mcd extends Object
Miner-Ciardo-Donatelli approximate stationary analysis.

Solve a structured CTMC whose EXACT reachable state space is stored in a decision diagram, by building and iterating K level-CTMCs (a decision-diagram-guided aggregation), after A.S. Miner, G. Ciardo, S. Donatelli, "Using the exact state space of a Markov model to compute approximate stationary measures", SIGMETRICS 2000.

The method never forms the |S|-state generator or probability vector. It keeps one CTMC per decision-diagram level k, over states M_k = {(p,i_k)} with p a level-k node and i_k a local state on a non-null arc, and iterates the coupled system to a fixed point. The single approximation (Eq. 5) is Pr{i_k | alpha} = Pr{i_k | p}: the local-state law at level k depends only on the node p, not the full path above it, which the exact reachability the diagram encodes justifies. For product-form models the method is EXACT (paper Sec. 5), so on a single-class closed QN it reproduces SolverCTMC.

Orientation. The paper indexes levels K (top/root) down to 1 (bottom/terminal); MDD uses level 0 as the root. This class works in the paper's orientation with 0-based indices, so paper level k (0 = bottom) maps to MDD level K-1-k and to station K-1-k. Getting this backwards silently mislabels every per-station metric.

  • Method Details

    • mdd_mcd

      public static MddMcdResult mdd_mcd(MddStruct mdds, MddDescriptor desc)
      Run the aggregation with the default level-iteration knobs.

    • mdd_mcd

      public static MddMcdResult mdd_mcd(MddStruct mdds, MddDescriptor desc, MddMcdOptions options)
      Approximate stationary measures by decision-diagram-guided aggregation.
      Parameters:
      mdds - the reachable set, in MDD orientation
      desc - the Kronecker rate descriptor
      options - level-iteration knobs