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== Abstract ==
 
== Abstract ==
  
This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum endtoend delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering. 5th IFIP International Conference on Network Control & Engineering for QoS, Security and Mobility Red de Universidades con Carreras en Informática (RedUNCI)
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This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum end-to-end delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.
 
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Document type: Part of book or chapter of book
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== Full document ==
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<pdf>Media:Draft_Content_834174704-beopen778-1514-document.pdf</pdf>
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* [https://link.springer.com/content/pdf/10.1007%2F978-0-387-34827-8_9.pdf https://link.springer.com/content/pdf/10.1007%2F978-0-387-34827-8_9.pdf]
 
* [https://link.springer.com/content/pdf/10.1007%2F978-0-387-34827-8_9.pdf https://link.springer.com/content/pdf/10.1007%2F978-0-387-34827-8_9.pdf]
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* [http://www.springerlink.com/index/pdf/10.1007/978-0-387-34827-8_9 http://www.springerlink.com/index/pdf/10.1007/978-0-387-34827-8_9],
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: [http://dx.doi.org/10.1007/978-0-387-34827-8_9 http://dx.doi.org/10.1007/978-0-387-34827-8_9]
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* [https://link.springer.com/chapter/10.1007/978-0-387-34827-8_9 https://link.springer.com/chapter/10.1007/978-0-387-34827-8_9],
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: [https://dblp.uni-trier.de/db/conf/ifip6-2/ifip6-2-2006.html#PintoB06 https://dblp.uni-trier.de/db/conf/ifip6-2/ifip6-2-2006.html#PintoB06],
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: [https://rd.springer.com/chapter/10.1007/978-0-387-34827-8_9 https://rd.springer.com/chapter/10.1007/978-0-387-34827-8_9],
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: [https://academic.microsoft.com/#/detail/1862226204 https://academic.microsoft.com/#/detail/1862226204]

Latest revision as of 16:58, 21 January 2021

Abstract

This work presents a multiobjective algorithm for multicast traffic engineering. The proposed algorithm is a new version of MultiObjective Ant Colony System (MOACS), based on Ant Colony Optimization (ACO). The proposed MOACS simultaneously optimizes the maximum link utilization, the cost of the multicast tree, the averages delay and the maximum end-to-end delay. In this way, a set of optimal solutions, known as Pareto set is calculated in only one run of the algorithm, without a priori restrictions. Experimental results obtained with the proposed MOACS were compared to a recently published Multiobjective Multicast Algorithm (MMA), showing a promising performance advantage for multicast traffic engineering.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1007/978-0-387-34827-8_9
https://dblp.uni-trier.de/db/conf/ifip6-2/ifip6-2-2006.html#PintoB06,
https://rd.springer.com/chapter/10.1007/978-0-387-34827-8_9,
https://academic.microsoft.com/#/detail/1862226204
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Document information

Published on 01/01/2006

Volume 2007, 2006
DOI: 10.1007/978-0-387-34827-8_9
Licence: CC BY-NC-SA license

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