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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 | + | 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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* [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], | ||
| + | : [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], | ||
| + | : [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], | ||
| + | : [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], | ||
| + | : [https://academic.microsoft.com/#/detail/1862226204 https://academic.microsoft.com/#/detail/1862226204] | ||
Latest revision as of 15:58, 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.
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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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