Smalltalk80LanguageImplementation:Chapter 22 - Revision history

Onionmixer: 오타수정

2015-07-13T10:17:56Z

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← Older revision		Revision as of 10:17, 13 July 2015
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	Repetition of the two messages delayUntil: and newProcessFor: depends on a probability distribution function. The number of repetitions equals the number of times the distribution can be sampled. The number that is sampled represents the next time that the sequence of actions (aBlock)		Repetition of the two messages delayUntil: and newProcessFor: depends on a probability distribution function. The number of repetitions equals the number of times the distribution can be sampled. The number that is sampled represents the next time that the sequence of actions (aBlock) should be invoked. Elements of the distribution are enumerated by sending the distribution the message do:.


	should be invoked. Elements of the distribution are enumerated by sending the distribution the message do:.

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Onionmixer: 정오표 수정

2014-05-09T09:40:03Z

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← Older revision		Revision as of 09:40, 9 May 2014
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	When a SimulationObject is synchronizing its tasks with that of another SimulationObject, it might be useful to know whether such an object is available. Two additional inquiry messages support finding out whether a provider or requester of a coordinated task is available--numberOfProvidersOfResource: resourceName and ~~numberOf-RequestersOfResource~~: resourceName.		When a SimulationObject is synchronizing its tasks with that of another SimulationObject, it might be useful to know whether such an object is available. Two additional inquiry messages support finding out whether a provider or requester of a coordinated task is available--numberOfProvidersOfResource: resourceName and numberOfRequestersOfResource: resourceName.


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	\|release: aStaticResource\|\|The receiver has been using the resource referred to by the argument, aStaticResource. It is no longer needed and can be recycled.		\|release: aStaticResource\|\|The receiver has been using the resource referred to by the argument, aStaticResource. It is no longer needed and can be recycled.
	\|- style="vertical-align:top;"		\|- style="vertical-align:top;"
	\|inquireFor: amount ~~ofRecsource~~: resourceName\|\|Answer whether or not the simulation has at least a quantity, amount, of a resource referred to by the String, resourceName.		\|inquireFor: amount ofResource: resourceName\|\|Answer whether or not the simulation has at least a quantity, amount, of a resource referred to by the String, resourceName.
	\|- style="vertical-align:top;"		\|- style="vertical-align:top;"
	\|resourceAvailable: resourceName\|\|Answer whether or not the simulation has a resource referred to by the String, resourceName.		\|resourceAvailable: resourceName\|\|Answer whether or not the simulation has a resource referred to by the String, resourceName.
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	\| colspan="2" \|simulation control		\| colspan="2" \|simulation control
	\|- style="vertical-align:top;"		\|- style="vertical-align:top;"
	\|~~startUP~~\|\|Specify the initial simulation objects and the arrival schedule of new objects.		\|startUp\|\|Specify the initial simulation objects and the arrival schedule of new objects.
	\|- style="vertical-align:top;"		\|- style="vertical-align:top;"
	\|proceed\|\|This is a single event execution. The first event in the queue, if any, is removed, time is updated to the time of the event, and the event is initiated.		\|proceed\|\|This is a single event execution. The first event in the queue, if any, is removed, time is updated to the time of the event, and the event is initiated.
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	In order to solve the first problem, the ~~Simulationmaintains~~ a queue of all the scheduled events. This queue is a SortedCollection whose elements are the events, sorted with respect to the simulated time in which they must be invoked. Each event on the queue is placed there within a package that is an instance of class DelayedEvent. At the time the package is created, the event is the system's active process. As such, it can be stored with its needed running context by creating a Semaphore. When the event is put on the queue, the DelayedEvent is sent the message pause which sends its Semaphore the message wait; when the event is taken off the queue, it is continued by sending it the message resume. The method associated with resume sends the DelayedEvent's Semaphore the message signal.		In order to solve the first problem, the Simulation maintains a queue of all the scheduled events. This queue is a SortedCollection whose elements are the events, sorted with respect to the simulated time in which they must be invoked. Each event on the queue is placed there within a package that is an instance of class DelayedEvent. At the time the package is created, the event is the system's active process. As such, it can be stored with its needed running context by creating a Semaphore. When the event is put on the queue, the DelayedEvent is sent the message pause which sends its Semaphore the message wait; when the event is taken off the queue, it is continued by sending it the message resume. The method associated with resume sends the DelayedEvent's Semaphore the message signal.


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	ifFalse: [resources add: (ResourceProvider named: resourceName with: amount)]		ifFalse: [resources add: (ResourceProvider named: resourceName with: amount)]
	coordinate: resourceName		coordinate: resourceName
	(self includesResourceFor: ~~resourceaName~~)		(self includesResourceFor: resourceName)
	ifFalse: [resources add: (ResourceCoordinator named: resourceName)]		ifFalse: [resources add: (ResourceCoordinator named: resourceName)]
	schedule: actionBlock after: timeDelay		schedule: actionBlock after: timeDelay
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	The key methods are the ones associated with schedule: aBlock at: timeInteger and schedule: aBlock startingAt: timeInteger andThenEvery: aProbabilityDistribution. This second message is a private one called by the method associated with scheduleArrivalOf: ~~aSimulationOb]ectClass~~ accordingTo: aProbabilityDistribution startingAt: timeInteger. It provides a general mechanism for scheduling repeated actions and therefore represents a solution to the third design problem mentioned earlier, how we implement the request to repeatedly schedule a sequence of actions.		The key methods are the ones associated with schedule: aBlock at: timeInteger and schedule: aBlock startingAt: timeInteger andThenEvery: aProbabilityDistribution. This second message is a private one called by the method associated with scheduleArrivalOf: aSimulationObjectClass accordingTo: aProbabilityDistribution startingAt: timeInteger. It provides a general mechanism for scheduling repeated actions and therefore represents a solution to the third design problem mentioned earlier, how we implement the request to repeatedly schedule a sequence of actions.


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	<syntaxhighlight lang="smalltalk">		<syntaxhighlight lang="smalltalk">
	private		private
	schedule: ~~ablock~~		schedule: aBlock
	startingAt: timeInteger		startingAt: timeInteger
	andThenEvery: aProbabilityDistribution		andThenEvery: aProbabilityDistribution
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	Step 1. newProcessFor: increments the processCount (self startProcess) and then creates a new Process that evaluates the ~~folloing~~ block, which will be referred to as block A.		Step 1. newProcessFor: increments the processCount (self startProcess) and then creates a new Process that evaluates the following block, which will be referred to as block A.

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Onionmixer: 오타수정

2014-05-09T08:49:17Z

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← Older revision		Revision as of 08:49, 9 May 2014
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	The method for the private message schedule: aBlock startingAt: ~~timelnteger~~ andThenEvery: aProbabilityDistribution forks a process that repeatedly schedules actions. The algorithm consists of iterations of two messages,		The method for the private message schedule: aBlock startingAt: timeInteger andThenEvery: aProbabilityDistribution forks a process that repeatedly schedules actions. The algorithm consists of iterations of two messages,

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Onionmixer: 내용 오류 수정

2014-04-28T15:22:37Z

내용 오류 수정

← Older revision		Revision as of 15:22, 28 April 2014
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	;Chapter ~~21 Probability Distributions~~		;Chapter 22 Event-Driven Simulations

	==~~Probability Distributions~~==		==Event-Driven Simulations==

	A simulation is a representation of a system of objects in a real or fantasy world. The purpose of creating a computer simulation is to provide a framework in which to understand the simulated situation, for example, to understand the behavior of a waiting line, the workload of clerks, or the timeliness of service to customers. Certain kinds of simulations are referred to as "counter simulations." They represent situations for which there are places or counters in which clerks work. Customers arrive at a place in order to get service from a clerk. If a clerk is not available, the customer enters a waiting line. The first customer in the line is serviced by the next available clerk. Often a given simulation has several kinds of places and several customers, each with an agenda of places to visit. There are many examples of such situations: banks, car washes, barber shops, hospitals, cafeterias, airports, post offices, amusement parks, and factories. A computer simulation makes it possible to collect statistics about these situations, and to test out new ideas about their organization.		A simulation is a representation of a system of objects in a real or fantasy world. The purpose of creating a computer simulation is to provide a framework in which to understand the simulated situation, for example, to understand the behavior of a waiting line, the workload of clerks, or the timeliness of service to customers. Certain kinds of simulations are referred to as "counter simulations." They represent situations for which there are places or counters in which clerks work. Customers arrive at a place in order to get service from a clerk. If a clerk is not available, the customer enters a waiting line. The first customer in the line is serviced by the next available clerk. Often a given simulation has several kinds of places and several customers, each with an agenda of places to visit. There are many examples of such situations: banks, car washes, barber shops, hospitals, cafeterias, airports, post offices, amusement parks, and factories. A computer simulation makes it possible to collect statistics about these situations, and to test out new ideas about their organization.

Onionmixer: SMALLTALK80 Chapter 21 Probability Distributions 페이지 추가

2014-04-28T15:21:38Z

SMALLTALK80 Chapter 21 Probability Distributions 페이지 추가

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