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Deterministic On-Line Routing on Area-Universal Networks

dc.contributor.authorBay, Paul Edwinen_US
dc.contributor.authorBilardi, Gianfrancoen_US
dc.date.accessioned2007-04-23T17:55:31Z
dc.date.available2007-04-23T17:55:31Z
dc.date.issued1991-09en_US
dc.description.abstractTwo deterministic routing networks are presented: the pruned butterfly and the sorting fattree. Both networks are area-universal, i.e., they can simulate any other routing network fitting in similar area with polylogarithmic slowdown. Previous area-universal networks were either for the off-line problem, where the message set to be routed is known in advance and substantial precomputation is permitted, or involved randomization, yielding results that hold only with high probability. The two networks introduced here are the first that are simultaneously deterministic and on-line, and they use two substantially different routing techniques. The performance of their routing algorithms depends on the difficulty of the problem instance, which is measured by a quantity $\lambda$ known as the load factor. The pruned butterfly algorithm runs in time $O$($\lambda$ log$^{2}$ $N$), where $N$ is the number of possible sources and detinations for messages and $\lambda$ is assumed to be poylnomial in $N$. The sorting fat-tree algorithm runs in $O$ ($\lambda$ log $N$ + log$^{2}$ $N$) time for a restricted class of message sets including partial permutations. Other results of this work include a new type of sorting circuit and an area-time lower bound for routers.en_US
dc.format.extent2983753 bytes
dc.format.extent651394 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR91-1237en_US
dc.identifier.urihttps://hdl.handle.net/1813/7077
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleDeterministic On-Line Routing on Area-Universal Networksen_US
dc.typetechnical reporten_US

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