All Classes and Interfaces
Class
Description
An element modeling an individual service activity
A class modeling precedence relationships among activities
Constants for defining activity precedences in LayeredNetwork models
Handler for the solver_amva function.
Handler for the solver_amvald function
An acyclic phase type distribution
A Bernoulli distribution
A Binomial distribution
Input buffer of a station
A class switch node based on cache hits or misses
APIs for stochastic models of caches
A class switcher section recording cache hits and misses
Examples of caching models
A task that offers caching services
Constants for defining calls in LayeredNetwork models
Examples of response time distribution analysis.
A class modelling a set of reachable classes for a given job (a chain)
A node that switches the class of an incoming job based on a probability table
A job class switcher based on a static probability table
Examples of models with class switching
Class representing a probabilistic routing matrix
Command line interface for JAR-based execution
Class where jobs perpetually loop without arriving or leaving (Closed class)
Examples of closed queueing networks
An abstract class for continuous distributions
A Coxian distribution with 2 phases.
A general Coxian distribution with n phases.
Examples of models with polling
An infinite server station, i.e.
A Deterministic distribution taking a single constant value.
A special distribution to denote disabled service or arrival.
Class of jobs that perpetually loop at a given station
An abstract class for discrete distributions.
A class for discrete distributions specified from the probability mass function
A discrete distribution that samples uniformly among a set of elements.
Output section that routes jobs to nodes
An abstract class of a general distribution
Client for Docker-based execution
Constants for specifying drop strategies at stations
Superclass for model elements
A section that models enabling conditions in a stochastic Petri net transition
A model defined by a collection of sub-models
Service exposed by a Task object
An environment model defined by a collection of network sub-models coupled with an environment transition rule
that selects the active sub-model.
An Erlang-n distribution with n phases.
Class abstracting an event within a Network model
A class storing events
A data structure acting as a key to the EventCache
Constants for specifying events
An exponential distribution.
Class representing the features of a particular solver
Collection of stations with constraints on the number of admitted jobs
Output section that models the process of firing for a transition in a Stochastic Petri net model
API for the methods used to deal with fork-join (FJ) systems, especially in the MVA solver.
A node that forks an incoming job into a set of sibling tasks
Output section that forks incoming jobs into sibling tasks
Examples of models with fork-join subsystems
Function wrapper class, allowing us to add and multiply using the complex high-precision Apcomplex by overriding UnaryOperator
Code was adapted from ...
Gallery of simple and classical queueing models
A Gamma distribution.
A Geometric distribution.
Getting started examples
Global constants for tolerances and solver configuration
A processor that can run Tasks
A hyper-exponential distribution.
An Immediate distribution that always samples 0.
A service section with an infinite number of servers (pure delay)
Examples of model initialization
Functions to print on screen
Input section of a station
A caching service that gives access to items
A set of cacheable items
Superclass representing a class of jobs
Constants for specifying a class of jobs
A node that reassembles a set of sibling tasks into the original parent job
Input section of a join node
Constants for specifying a join strategy
Examples of layered networks
A layered queueing network model
Element of a LayeredNetwork model
Class summarizing the characteristics of a LayeredNetwork
The LineCLI class provides a command-line interface for configuring and running the LINE Solver.
LineClient is a WebSocket client used to communicate with the LINE Solver server.
LineServer is a WebSocket server that receives client connections, processes incoming messages,
and interacts with the LINE Solver.
Output section of a Place in a Stochastic Petri net model
Examples of models with load-dependent stations
A node that logs passage of jobs
A Lognormal distribution.
A section that forwards jobs without introducing delays in a Log node
APIs for stochastic models of loss networks
APIs for stochastic point processes
A Markovian Arrival Process
An abstract class for marked point processes
A Marked Markovian Arrival Process
A Marked Markov-Modulated Poisson Process (M3PP)
An abstract class for a Markovian distribution
An abstract class for a Markov-modulated point-process
Mathematical functions and utilities.
A sparse matrix data structure supporting linear algebra functions similar to those available in MATLAB.
A ordered list of Matrix objects
A class that extends EJML's Equation to use jline.util.Matrix
APIs for Markov Chains.
Constants for specifying a Metric
Constants for specifying a type of metric
Miscellaneous examples
Examples of mixed queueing networks
A Markovian-modulated Poisson Process with 2 states
Superclass representing a class of jobs
Class representing a model supported by the library
Methods for model-to-model transformation
Handler for the solver_mva function.
Handler for the solver_mvald function.
A class to store a named parameter.
A queueing network model
Class for auxiliary information stored in Network objects
Class representing an element within a Network object
Class summarizing the characteristics of a Network object
Superclass for a node element within a Network model
Auxiliary class for information stored within a Node object
Class for the nodeparam field within NetworkStruct
Constants for specifying the type of a Node
APIs for evaluating non-product-form queueing networks.
A class of jobs that arrives from the external world to the Network and, after completion, leaves it
Examples of open queueing networks
Output section of a node
Class modelling the output section of a Node
A pair of objects of different classes.
A Pareto distribution
APIs for evaluating Product-Form Queueing Networks.
A general phase-type (PH) distribution
A queueing station within a Network model
A Poisson discrete distribution
APIs for evaluating polling systems.
A service section that processes jobs using Polling scheduling
Data structure modeling a lattice used to describe a combination of job populations.
A preemptive service section
Examples of queueing models with priorities
Alias for the Host class, i.e., a processor that can run Tasks
Constants for specifying a point process type
APIs for evaluating queueing systems such as M/M/1, M/M/k, M/G/1, and others.
A queueing station within a Network model
Examples of models evolving in a random environment
Input buffer of a Source
Constants for specifying a cache replacement strategy
A class that replays values in order from a trace file
Return classes
Represents the return type for the cache gamma linear program computations.
Represents the return type for cache miss rate computations with the ray method.
Represents the return type for the cache MVA (Mean Value Analysis) computations.
Represents the return type for cache ray method.
Represents the return type for the cache xi fixed-point algorithm computations.
A class modelling the output of afterEvent* functions
Constructs a lossnErlangFPReturn object with the specified queue-length, loss probability,
blocking probability, and iteration count.
Class representing the return type for the fitting of a 2-phase APH (Acyclic Phase-Type) distribution.
A class to represent the return type of the map2_fit function, holding the transition matrices and possibly other fitting results.
Class representing the return type for fitting a mixture model to a MMAP.
Constructor initializing the sample data, number of types, and type indices.
Data structure to return the results of non-product-form queueing network approximation.
Data structure for storing results from the AMVA (Approximate Mean Value Analysis) method.
Data structure for storing results from the AMVA MS (Approximate Mean Value Analysis
Multiservice) method.
Data structure for storing results the COMOM method.
Data structure for storing results from the load-dependent COMOM method.
Data structure for storing linearizer core results from a queueing network analysis.
Function class for the integrand used in cubature calculations.
Data structure for storing linearizer estimtate results from a queueing network analysis.
Data structure for storing results from a FNC (Fitting Normalizing Constants) calculation.
Data structure for storing linearizer forward results from a queueing network analysis.
Auxiliary class used to index interim results in pfqn_gld.
Data structure for storing results from a fixed-point iteration method.
Data structure for storing results from a fixed-point iteration method with normalization.
Data structure for storing results from the core linearizer method.
Data structure for storing intermediate estimates from the linearizer method.
Data structure for storing final results from the forward MVA step in the linearizer method.
Data structure for storing core results from the MS linearizer method.
Data structure for storing estimated intermediate results from the MS linearizer method.
Data structure for storing final results from the forward MVA step of the MS linearizer method.
Data structure to hold the results of the MVA (Mean Value Analysis) computation.
Data structure for storing results from an MVA computation using the LD method.
Data structure to hold the results of the MVA computation with additional detailed metrics.
Data structure to hold extended results from the MVA computation, particularly
focusing on error corrections.
Data structure for storing results from a normalizing constant calculation.
Data structure for storing complex results from a normalizing constant calculation.
Data structure for storing sanitized input parameters for a normalizing constant calculation.
Data structure for storing results from a normalizing constant calculation involving throughputs and
queue lengths.
Data structure for storing results from the RD method.
A class to store the results of queueing system analysis.
A return type for the snDeaggregateChainResults method, encapsulating multiple chain-related matrix results.
A return type for the snGetDemands method, encapsulating multiple matrix results.
A return type for the snGetDemandsChain method, encapsulating multiple chain-related matrix results.
A return type for methods returning product form chain parameters.
A return type for methods returning product form parameters.
Examples of reinforcement learning algorithms for routing
A node that routes jobs without imposing any delay
Class representing a probabilistic routing matrix
Constants for specifying routing strategies at stations
Constants for specifying scheduling strategies at stations
Constants for specifying a scheduling strategy type at stations
Examples of layered networks
A general class modeling a node section
Class of jobs that perpetually loop at a given station
Interface used for routing functions
A service section that processes jobs
A class for associating job classes, service strategies and distributions
A station with a service process
A section offering a service
A station with a service process
Constants for specifying service strategies at stations
A section that forwards jobs without introducing delays in a service station
A server shared by multiple jobs simultaneously
An abstraction of the external world jobs in open classes depart to
APIs to process NetworkStruct objects.
MVA Analyzer class
MVA Analyzer class for bounding methods
MVA Analyzer class for non-rentrant caches
MVA Analyzer class for solver_mva_cacheqn_analyzer
MVALD Analyzer
MVA Query System analyzer
Constants for specifying a named solver
An abstraction of the external world jobs in open classes come from
Class modeling the state of Stateful nodes
Examples of models with state-dependent routing
A class switcher that depends on its local state
A node that can have a state
A class switcher that does not have a local state
Examples of state probability computations
A node where jobs can spend time stationing there
Examples of stochastic Petri net models
Input buffer of a Place in a Stochatic Petri net model
Examples of models with switchover times
A declaration of a synchronization on a NetworkEvent
Functions for interfacing with JMT, JLQN, and the operating system
A LayeredNetwork entity that can host services specified in the form of Entry objects and that runs on a Host
Assorted test models
A class for random number generation in separate threads
A service section of a Transition in a stochastic Petri net model
Constants for specifying timing strategies at Petri net transitions
Alias for the Replayer class
APIs for statistical analysis of trace data.
Transition as in a stochastic Petri net model
An undirected graph used for routing and class-switching matrices.
A continuous Uniform distribution
Miscellaneous utilities
Constants for specifying a solver verbosity level
A Weibull distribution
A Zipf-like probability distribution