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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 IEEE Networkarrow_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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Article . 1999 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Article . 2021
Data sources: DBLP
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Spawning networks

Authors: Andrew T. Campbell; Michael E. Kounavis; Daniel A. M. Villela; John B. Vicente; Hermann de Meer; Kazuho Miki; K. S. Kalaichelvan;

Spawning networks

Abstract

The deployment of new network architectures, services, and protocols is often manual, ad hoc, and time-consuming. We introduce "spawning networks," a new class of programmable networks that automate the life cycle process for the creation, deployment, and management of network architectures. These networks are capable of spawning distinct "child" virtual networks with their own transport, "parent's" network resources and in isolation from other spawned networks. Spawned child networks represent programmable virtual networks and support the controlled access to communities at users with specific connectivity, security, and quality of service requirements. In this article we present a framework for the realization of spawning networks based on the notion of the Genesis Kernel, a virtual network operating system capable of creating distinct virtual network architectures on the fly. We discuss the motivation and principles that underpin spawning networks and focus on the design of the transport, programming and life cycle environments, which comprise the main architectural components of the Genesis Kernel.

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    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.
    Average
    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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    impulse
    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!
34
Average
Top 10%
Top 10%
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