Package jline.examples.java.advanced
Class StateProbabilitiesExamples
java.lang.Object
jline.examples.java.advanced.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.
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionstatic voidMain method to run all state probability examples.static voidDemonstrates aggregated state probabilities (statepr_aggr.ipynb).static voidDemonstrates aggregated state probabilities for large systems (statepr_aggr_large.ipynb).static voidDemonstrates all state probabilities for FCFS queues (statepr_allprobs_fcfs.ipynb).static voidDemonstrates all state probabilities for PS queues (statepr_allprobs_ps.ipynb).static voidDemonstrates system-wide aggregated state probabilities (statepr_sys_aggr.ipynb).static voidDemonstrates system-wide aggregated probabilities for large systems (statepr_sys_aggr_large.ipynb).
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Constructor Details
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StateProbabilitiesExamples
public StateProbabilitiesExamples()
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Method Details
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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- Throws:
Exception- if the solver encounters an error
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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- Throws:
Exception- if the solver encounters an error
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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- Throws:
Exception- if the solver encounters an error
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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- Throws:
Exception- if the solver encounters an error
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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- Throws:
Exception- if the solver encounters an error
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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- Throws:
Exception- if the solver encounters an error
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main
Main method to run all state probability examples.- Parameters:
args- command line arguments (not used)
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