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Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame
Dissertation (MEng)--University of Pretoria, 2013.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2014
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| _version_ | 1867613547175870464 |
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| access_status_str | Open Access |
| author2 | Grobler, H. |
| author_browse | Grobler, H. |
| author_facet | Grobler, H. |
| collection | Thesis |
| dc_rights_str_mv | © 2013 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Dissertation (MEng)--University of Pretoria, 2013. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/33345 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:37:52.763Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/33345 Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame Grobler, H. Van Wyk, J.H. (Jacques Herman) Botha, Marthinus Ignatius Automated main distribution frame Neural networks OMNeT++ Redundancy optimisation Redundancy allocation problem Expected lifetime System reliability Hybrid intelligent algorithm Genetic algorithm Stochastic simulation UCTD Dissertation (MEng)--University of Pretoria, 2013. Maintaining and operating manual main distribution frames is labour-intensive. As a result, Automated Main Distribution Frames (AMDFs) have been developed to alleviate the task of maintaining subscriber loops. Commercial AMDFs are currently employed in telephone exchanges in some parts of the world. However, the most significant factors limiting their widespread adoption are costeffective scalability and reliability. Therefore, an impelling incentive is provided to create a simulation framework in order to explore typical implementations and scenarios. Such a framework will allow the evaluation and optimisation of a design in terms of both internal and external redundancies. One of the approaches to improve system performance, such as system reliability, is to allocate the optimal redundancy to all or some components in a system. Redundancy at the system or component levels can be implemented in one of two schemes: parallel redundancy or standby redundancy. It is also possible to mix these schemes for various components. Moreover, the redundant elements may or may not be of the same type. If all the redundant elements are of different types, the redundancy optimisation model is implemented with component mixing. Conversely, if all the redundant components are identical, the model is implemented without component mixing. The developed framework can be used both to develop new AMDF architectures and to evaluate existing AMDF architectures in terms of expected lifetimes, reliability and service availability. Two simulation models are presented. The first simulation model is concerned with optimising central office equipment within a telephone exchange and entails an environment of clients utilising services. Currently, such a model does not exist. The second model is a mathematical model incorporating stochastic simulation and a hybrid intelligent evolutionary algorithm to solve redundancy allocation problems. For the first model, the optimal partitioning of the model is determined to speed up the simulation run efficiently. For the second model, the hybrid intelligent algorithm is used to solve the redundancy allocation problem under various constraints. Finally, a candidate concept design of an AMDF is presented and evaluated with both simulation models. gm2014 Electrical, Electronic and Computer Engineering unrestricted 2014-02-11T05:11:59Z 2014-02-11T05:11:59Z 2013-09-04 2013 Dissertation Botha, MI 2013, Modelling and simulation framework incorporating redundancy and failure probabilities fir evaluation of a modular automated main distribution frame, MEng dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/33345> E13/9/1017/gm http://hdl.handle.net/2263/33345 en © 2013 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | Automated main distribution frame Neural networks OMNeT++ Redundancy optimisation Redundancy allocation problem Expected lifetime System reliability Hybrid intelligent algorithm Genetic algorithm Stochastic simulation UCTD Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| title | Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| title_full | Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| title_fullStr | Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| title_full_unstemmed | Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| title_short | Modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| title_sort | modelling and simulation framework incorporating redundancy and failure probabilities for evaluation of a modular automated main distribution frame |
| topic | Automated main distribution frame Neural networks OMNeT++ Redundancy optimisation Redundancy allocation problem Expected lifetime System reliability Hybrid intelligent algorithm Genetic algorithm Stochastic simulation UCTD |
| url | http://hdl.handle.net/2263/33345 |