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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 https://doi.org/10.1...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
https://doi.org/10.1109/gcwksh...
Article . 2019 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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In-Packet Network Coding for Effective Packet Wash and Packet Enrichment

Authors: Richard Li; Lijun Dong;

In-Packet Network Coding for Effective Packet Wash and Packet Enrichment

Abstract

Packets could be dropped completely in the current Internet if there is not enough buffer in the routers due to network congestion or packet error happens during the transmission. This practice causes re-transmissions of the packets under the reliable transmission protocols, which in-turn produces unwanted delay , reduces throughput, and wastes network resources. Recently, a new network service called Qualitative Communication suggests to avoid entire packet dropping, instead breaking the packet into smaller logical units (chunks). The network nodes (e.g. routers) could perform packet scrubbing on the packet with the granularity of chunks, such operation is named as Packet Wash. In this paper, we propose to apply random linear network coding on the chunks of the packet payload to enable the packet wash and packet enrichment in the network. The benefits of utilizing such packetization are discussed in the paper.

  • BIP!
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    citations
    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).
    18
    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.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
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!
18
Top 10%
Top 10%
Top 10%
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