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Priority-Enabled Optimization of Resource Utilization in Fault-Tolerant Optical Transport Networks

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High Performance Computing and Communications (HPCC 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4208))

Abstract

In this paper, a novel SCMTO heuristic algorithm of establishing survivable connections in wide-area networks, that jointly optimizes the level of resource utilization as well as the time of connection restoration, is proposed. The algorithm is dedicated to multipriority traffic. Two service classes are assumed, referred to as low and high priority, respectively. Unlike typical optimization methods, SCMTO algorithm also guarantees fast service restoration by processing the high-priority connections with the author’s a posteriori optimization, based on the Largest-First graph coloring heuristics.

The algorithm was evaluated for the US Long-Distance Network. The results show that with only little capacity utilization degradation, fast restoration can be achieved. Compared to the results of the typical a priori optimization, the obtained average values of connection restoration time were up to 20% shorter (and even up to 41% for the high-priority traffic only). They were achieved together with reduction in resource utilization ratio up to 48%.

Presented solutions are dedicated to WDM-based high-performance optical communications network architectures.

This work is partially supported by the Ministry of Education and Science, Poland, under the grant 3 T11D 001 30.

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Rak, J. (2006). Priority-Enabled Optimization of Resource Utilization in Fault-Tolerant Optical Transport Networks. In: Gerndt, M., Kranzlmüller, D. (eds) High Performance Computing and Communications. HPCC 2006. Lecture Notes in Computer Science, vol 4208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11847366_89

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  • DOI: https://doi.org/10.1007/11847366_89

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39368-9

  • Online ISBN: 978-3-540-39372-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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