Package jline.api

package jline.api
Procedural algorithms for solving stochastic models and analyzing queueing systems.

This package provides low-level algorithmic implementations for various analysis methods used in queueing theory, stochastic modeling, and performance evaluation. The algorithms are organized into specialized subpackages based on the modeling domain and analysis technique.

Subpackages

  • jline.api.cache - Cache modeling algorithms (LRU, TTL, hit/miss probabilities)
  • jline.api.lossn - Loss network algorithms (Erlang formulas, blocking probabilities)
  • jline.api.lsn - Layered stochastic network (LayeredNetworkStruct) data structure manipulation
  • jline.api.mam - Matrix Analytic Methods (MAP, APH, MMAP processes)
  • jline.api.mapqn - MAP-based queueing network analysis algorithms
  • jline.api.mc - Markov Chain algorithms (CTMC, DTMC analysis)
  • jline.api.measures - Distance and similarity metrics for performance analysis
  • jline.api.npfqn - Non-Product Form Queueing Network algorithms
  • jline.api.pfqn - Product Form Queueing Network algorithms (MVA, convolution, normalizing constant, load-dependent)
  • jline.api.polling - Polling system algorithms (gated, exhaustive, limited service)
  • jline.api.qsys - Single queue system algorithms (M/M/1, M/G/1, GI/GI/1, etc.)
  • jline.api.rl - Reinforcement learning and optimization algorithms
  • jline.api.sn - Stochastic network data structure (NetworkStruct) manipulation
  • jline.api.trace - Trace analysis algorithms (moments, statistics)
  • jline.api.wf - Workflow and job scheduling analysis algorithms

Note: These are low-level procedural algorithms primarily implemented in Kotlin. For high-level object-oriented modeling, use the jline.lang package. For complete solvers, use the jline.solvers package.

Since:
LINE 2.0
See Also: