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https://doi.org/10.1109/allert...
Article . 2010 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2010
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
Article . 2010
Data sources: DBLP
DBLP
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On equivalence between network topologies

Authors: Tracey Ho; Michelle Effros; Shirin Jalali;

On equivalence between network topologies

Abstract

One major open problem in network coding is to characterize the capacity region of a general multi-source multi-demand network. There are some existing computational tools for bounding the capacity of general networks, but their computational complexity grows very quickly with the size of the network. This motivates us to propose a new hierarchical approach which finds upper and lower bounding networks of smaller size for a given network. This approach sequentially replaces components of the network with simpler structures, i.e., with fewer links or nodes, so that the resulting network is more amenable to computational analysis and its capacity provides an upper or lower bound on the capacity of the original network. The accuracy of the resulting bounds can be bounded as a function of the link capacities. Surprisingly, we are able to simplify some families of network structures without any loss in accuracy.

8 pages, 12 figures, 48th Annual Allerton Conference on Communication, Control, and Computing, 2010

Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT)

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    popularity
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    Average
    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
31
Average
Top 10%
Top 10%
Green