(Created page with " == Abstract == In Multi-Layer networks, where more than one layer is dynamic, i.e., connections are set up using not only the upper, e.g., IP layer but the underlying wavele...")
 
 
(One intermediate revision by the same user not shown)
Line 2: Line 2:
 
== Abstract ==
 
== Abstract ==
  
In Multi-Layer networks, where more than one layer is dynamic, i.e., connections are set up using not only the upper, e.g., IP layer but the underlying wavelength layer as well leads often to suboptimal performance due to long wavelength paths, that do not allow routing the traffic along the shortest path. The role of MLTE (Multi-Layer Traffic Engineering) is to cut these long wavelength paths into parts (fragments) that allow better routing at the upper layer (fragmentation), or to concatenate two or more fragments into longer paths (defragmentation) when the network load is low and therefore less hops are preferred.\r \r In this paper we present a new model (GG: Grooming Graph) and an algorithm for this model that supports Fragmentation and De-Fragmentation of wavelength paths making the network always instantly adapt to changing traffic conditions. We introduce the notion of shadow capacities to model “lightpath tailoring”. We implicitly assume that the wavelength paths carry such, e.g., IP traffic that can be interrupted for a few microseconds and that even allows minor packet reordering.\r \r To show the superior performance of our approach in various network and traffic conditions we have carried out an intensive simulation study.
+
In Multi-Layer networks, where more than one layer is dynamic, i.e., connections are set up using not only the upper, e.g., IP layer but the underlying wavelength layer as well leads often to suboptimal performance due to long wavelength paths, that do not allow routing the traffic along the shortest path. The role of MLTE (Multi-Layer Traffic Engineering) is to cut these long wavelength paths into parts (fragments) that allow better routing at the upper layer (fragmentation), or to concatenate two or more fragments into longer paths (defragmentation) when the network load is low and therefore less hops are preferred.   In this paper we present a new model (GG: Grooming Graph) and an algorithm for this model that supports Fragmentation and De-Fragmentation of wavelength paths making the network always instantly adapt to changing traffic conditions. We introduce the notion of shadow capacities to model “lightpath tailoring”. We implicitly assume that the wavelength paths carry such, e.g., IP traffic that can be interrupted for a few microseconds and that even allows minor packet reordering.   To show the superior performance of our approach in various network and traffic conditions we have carried out an intensive simulation study.
 
+
Document type: Part of book or chapter of book
+
 
+
== Full document ==
+
<pdf>Media:Draft_Content_673161157-beopen407-1578-document.pdf</pdf>
+
  
  
Line 15: Line 10:
  
 
* [https://link.springer.com/content/pdf/10.1007%2F11753810_60.pdf https://link.springer.com/content/pdf/10.1007%2F11753810_60.pdf]
 
* [https://link.springer.com/content/pdf/10.1007%2F11753810_60.pdf https://link.springer.com/content/pdf/10.1007%2F11753810_60.pdf]
 +
 +
* [http://link.springer.com/content/pdf/10.1007/11753810_60 http://link.springer.com/content/pdf/10.1007/11753810_60],
 +
: [http://dx.doi.org/10.1007/11753810_60 http://dx.doi.org/10.1007/11753810_60] under the license http://www.springer.com/tdm
 +
 +
* [https://dblp.uni-trier.de/db/conf/networking/networking2006.html#CinklerHAGSK06 https://dblp.uni-trier.de/db/conf/networking/networking2006.html#CinklerHAGSK06],
 +
: [https://link.springer.com/chapter/10.1007/11753810_60 https://link.springer.com/chapter/10.1007/11753810_60],
 +
: [https://www.scipedia.com/public/Cinkler_et_al_2006a https://www.scipedia.com/public/Cinkler_et_al_2006a],
 +
: [https://dx.doi.org/10.1007/11753810_60 https://dx.doi.org/10.1007/11753810_60],
 +
: [https://hungary.pure.elsevier.com/en/publications/multi-layer-traffic-engineering-through-adaptive-%CE%B3-path-fragmenta https://hungary.pure.elsevier.com/en/publications/multi-layer-traffic-engineering-through-adaptive-%CE%B3-path-fragmenta],
 +
: [https://academic.microsoft.com/#/detail/1485374431 https://academic.microsoft.com/#/detail/1485374431]

Latest revision as of 14:23, 21 January 2021

Abstract

In Multi-Layer networks, where more than one layer is dynamic, i.e., connections are set up using not only the upper, e.g., IP layer but the underlying wavelength layer as well leads often to suboptimal performance due to long wavelength paths, that do not allow routing the traffic along the shortest path. The role of MLTE (Multi-Layer Traffic Engineering) is to cut these long wavelength paths into parts (fragments) that allow better routing at the upper layer (fragmentation), or to concatenate two or more fragments into longer paths (defragmentation) when the network load is low and therefore less hops are preferred. In this paper we present a new model (GG: Grooming Graph) and an algorithm for this model that supports Fragmentation and De-Fragmentation of wavelength paths making the network always instantly adapt to changing traffic conditions. We introduce the notion of shadow capacities to model “lightpath tailoring”. We implicitly assume that the wavelength paths carry such, e.g., IP traffic that can be interrupted for a few microseconds and that even allows minor packet reordering. To show the superior performance of our approach in various network and traffic conditions we have carried out an intensive simulation study.


Original document

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

http://dx.doi.org/10.1007/11753810_60 under the license http://www.springer.com/tdm
https://link.springer.com/chapter/10.1007/11753810_60,
https://www.scipedia.com/public/Cinkler_et_al_2006a,
https://dx.doi.org/10.1007/11753810_60,
https://hungary.pure.elsevier.com/en/publications/multi-layer-traffic-engineering-through-adaptive-%CE%B3-path-fragmenta,
https://academic.microsoft.com/#/detail/1485374431
Back to Top

Document information

Published on 01/01/2006

Volume 2006, 2006
DOI: 10.1007/11753810_60
Licence: CC BY-NC-SA license

Document Score

0

Views 2
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?