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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao MAnnheim DOCument Se...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Conference object . 2016
https://doi.org/10.1109/cse-eu...
Article . 2016 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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Reliable Memory Efficient Name Forwarding in Named Data Networking

Authors: Divya Saxena; Vaskar Raychoudhury; Christian Becker 0001; Neeraj Suri;

Reliable Memory Efficient Name Forwarding in Named Data Networking

Abstract

Named Data Networking (NDN) is a promising future Internet architecture which retrieves the content using their names. Content names composed of strings separated by '/' are stored in the NDN Forwarding Information Base (FIB) to forward the incoming packets further. To retrieve content through their names poses two main challenges for the NDN FIB: high memory consumption and high lookup time. Therefore, an efficient and scalable data structure is required to store names in FIB. Encoding components in all the names with a unique integer can reduce the memory consumption as well as lookup time. In this paper, we propose a scalable and memory-efficient radix trie based name component encoding scheme, named RaCE, to implement NDN FIB. Our experiment results show that the RaCE scheme is reducing memory consumption by 89.95% and 26.07% compared to the original size of data and NCE [4] scheme for the 29 million dataset, respectively.

Countries
United Kingdom, Germany
Keywords

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
11
Top 10%
Top 10%
Top 10%
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