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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 Computer Communicati...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
Computer Communications
Article . 2015 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
DBLP
Article . 2020
Data sources: DBLP
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Hierarchical and hash based naming with Compact Trie name management scheme for Vehicular Content Centric Networks

Authors: Safdar Hussain Bouk; Syed Hassan Ahmed; Dongkyun Kim;

Hierarchical and hash based naming with Compact Trie name management scheme for Vehicular Content Centric Networks

Abstract

Content-Centric Network (CCN) is a promising future Internet architecture, attracting research community and being widely adopted in the vehicular networks. The main concept of CCN is to smoothly distribute digital contents between the content provider and consumer. In these types of networks, contents are identified by unique names, however, naming those contents is still a challenging task. Therefore, we propose a hierarchical and hash based naming with efficient Compact Trie (CT) management scheme for Vehicular Content-Centric Network (VCCN). The proposed naming scheme makes the best use of the features offered by hierarchical as well as hash-based or flat naming schemes. The hierarchical part of the digital content name contains information about the content provider, type, its sub-types and attributes of the content itself that is shared between vehicles. The hash part uniquely identifies the digital content required for VCCN applications. The proposed naming scheme satisfies two main purposes: first, it helps in minimizing the routing table by aggregating the name prefixes and simplifying the routing decisions. Second, it contains attributes, spatial, temporal and their range information to easily find and resolve the content. The proposed scheme manages prefixes (e.g. Add, Search and Delete) in the tables e.g. Forwarding Information Base (FIB), Pending Interest Table (PIT), etc. The CT is relatively faster and space-efficient than Simple Trie and has better performance compared to the existing solutions of naming the required content(s). The evaluation results show that the proposed CT based prefix management scheme performs 45.5% and 23.3% faster prefix search and 55% and 34% faster prefix delete operation compared to Simple Trie and Bloom-Filter based name management schemes, respectively. The memory profile results show that average memory consumption of the proposed CT implementation is 24 and 186 times smaller than the Simple Trie and the NLAPB, respectively.

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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!
48
Top 10%
Top 10%
Top 10%
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