Learning-based wavelength assignment in optical burst switching networks

Simple item page
dc.contributorGraduate Program in Computer Engineering.
dc.contributor.advisorZeren, Murat.
dc.contributor.authorKorçak, Ömer.
dc.date.accessioned2023-03-16T10:02:03Z
dc.date.available2023-03-16T10:02:03Z
dc.date.issued2004.
dc.description.abstractAs in any WDM network, the wavelength conversion capability of routers has a major effect on the performance of OBS networks. However, wavelength conversion is an immature and expensive technology and still remains as a topic of further study. Therefore assuming full wavelength convertibility is not a practical assumption. It is important to focus on avoiding burst drops in OBS networks with wavelength conversion incapable nodes, and efficient wavelength assignment is an important issue for this purpose. Wavelength assignment techniques proposed for Wavelength-Routed Networks are generally not suitable for OBS Networks and some distributed assignment techniques are needed to be devised. In this paper, we proposed a learning based wavelength assignment technique, namely LWA. We make some extensions to this technique via employing a preemption mechanism and using some features of OBS like burst aggregation, and show that the proposed techniques are suitable in order to reduce the burst drop probability, as well as supporting QoS and reducing the end-to-end delay.
dc.format.extent30cm.
dc.format.pagesxv, 85 leaves;
dc.identifier.otherCMPE 2004 K67
dc.identifier.urihttps://digitalarchive.library.bogazici.edu.tr/handle/123456789/12289
dc.publisherThesis (M.S.)-Bogazici University. Institute for Graduate Studies in Science and Engineering, 2004.
dc.subject.lcshWavelength division multiplexing.
dc.subject.lcshOptical communications.
dc.subject.lcshPacket switching (Data transmission)
dc.titleLearning-based wavelength assignment in optical burst switching networks

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
b1310491.007865.001.PDF
Size:
5.04 MB
Format:
Adobe Portable Document Format
Download

Collections

M.S. Theses