Package jline.examples.java.advanced

Class StateProbabilitiesExamples

  • All Implemented Interfaces:
    
public class StateProbabilitiesExamples

    Examples demonstrating state probability computations in queueing networks. This class provides Java implementations corresponding to the Kotlin notebooks in jline.examples.kotlin.advanced.stateProbabilities package.

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description

    • Field Summary

      Fields 
      Modifier and Type Field Description

    • Enum Constant Summary

      Enum Constants 
      Enum Constant Description

    • Method Summary

      Modifier and Type Method Description
      static void statepr_aggr() Demonstrates aggregated state probabilities (statepr_aggr.ipynb).
      static void statepr_aggr_large() Demonstrates aggregated state probabilities for large systems (statepr_aggr_large.ipynb).
      static void statepr_allprobs_fcfs() Demonstrates all state probabilities for FCFS queues (statepr_allprobs_fcfs.ipynb).
      static void statepr_allprobs_ps() Demonstrates all state probabilities for PS queues (statepr_allprobs_ps.ipynb).
      static void statepr_sys_aggr() Demonstrates system-wide aggregated state probabilities (statepr_sys_aggr.ipynb).
      static void statepr_sys_aggr_large() Demonstrates system-wide aggregated probabilities for large systems (statepr_sys_aggr_large.ipynb).
      static void main(Array<String> args) Main method to run all state probability examples.

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Constructor Detail

      • StateProbabilitiesExamples

        StateProbabilitiesExamples()

    • Method Detail

      • statepr_aggr

         static void statepr_aggr()

        Demonstrates aggregated state probabilities (statepr_aggr.ipynb). This example shows how to compute and analyze aggregated state probabilities, where states are grouped based on certain characteristics such as total number of customers or server occupancy patterns. Features: - State aggregation techniques - Marginal probability distributions - Efficient computation for large state spaces - Analysis of system-wide properties

      • statepr_aggr_large

         static void statepr_aggr_large()

        Demonstrates aggregated state probabilities for large systems (statepr_aggr_large.ipynb). This example extends the aggregated state probability analysis to larger systems where direct enumeration of all states is infeasible. It shows approximation techniques and efficient algorithms for large-scale analysis. Features: - Large state space handling - Approximation techniques for state probabilities - Memory-efficient algorithms - Scalability analysis

      • statepr_allprobs_fcfs

         static void statepr_allprobs_fcfs()

        Demonstrates all state probabilities for FCFS queues (statepr_allprobs_fcfs.ipynb). This example computes the complete state probability distribution for systems with FCFS queues. It shows how customer ordering affects the state space structure and probability calculations. Features: - Complete state enumeration for FCFS - Customer order tracking - Exact probability computation - Analysis of queue length distributions

      • statepr_allprobs_ps

         static void statepr_allprobs_ps()

        Demonstrates all state probabilities for PS queues (statepr_allprobs_ps.ipynb). This example computes state probabilities for processor sharing queues, where the state space is simpler than FCFS as customer ordering doesn't matter. This allows for more efficient computation and analysis. Features: - State space reduction for PS - Efficient probability computation - Comparison with FCFS state space - Product-form solution exploitation

      • statepr_sys_aggr

         static void statepr_sys_aggr()

        Demonstrates system-wide aggregated state probabilities (statepr_sys_aggr.ipynb). This example focuses on system-wide state aggregations, such as the probability of having exactly k customers in the entire network regardless of their distribution across nodes. Features: - System-wide state aggregation - Network-level performance metrics - Efficient computation methods - Little's Law validation

      • statepr_sys_aggr_large

         static void statepr_sys_aggr_large()

        Demonstrates system-wide aggregated probabilities for large systems (statepr_sys_aggr_large.ipynb). This example extends system-wide aggregation to large-scale networks where exact computation is challenging. It demonstrates approximation techniques and asymptotic analysis methods. Features: - Large-scale system aggregation - Asymptotic approximations - Computational complexity reduction - Accuracy vs. efficiency trade-offs

      • main

         static void main(Array<String> args)

        Main method to run all state probability examples.

        Parameters:
        args - command line arguments (not used)