Improved Time Representation in Discrete-Event Simulation

Discrete-Event Simulation (DES) is a technique in which the simulation engine plays a history following a chronology of events. The technique is called ”discrete-event” because the processing of each event of the chronology takes place at discrete points of a continuous time-line. In computer implementations, an event could be represented by a message, and a time occurrence. The message data type is usually defined as part of the model and the simulator algorithms do not operate with them. Opposite is the case of time variables; simulator has to interact actively with them for reproducing the chronology of events over R+, which is usually represented by approximated data types as floating-point. The approximation of time values in the simulation can affect the time-line preventing the generation of correct results. In addition, it is common to collect data from real systems to predict future phenomena, for example for weather forecasting. When collecting data using metrological instruments and procedures, the measurement results include uncertainty quantifications, usually defined as intervals. However, sometimes, answering a question requires evaluating the results of all values in the uncertainty interval. This thesis proposes data types for handling representation of time properly in DES, including irrational and periodic time values. Moreover, we propose a method for obtaining every possible simulation result of DES models when feeding them events with uncertainty quantification on their time component.

Name thesis:degree_name

Doctor of Philosophy (Ph.D.)

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Engineering, Electrical and Computer

Grantor dc:publisher

Carleton University

Year dc:date.issued

2016

Author dc:creator

• Vicino, Damian Alberto

Statement dc:rights

• Copyright © 2016 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.

Language dc:language.iso

en

DOI

10.22215/etd/2016-11231

OAI identifier oai:identifier

oai:carleton.scholaris.ca:20.500.14718/39308