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7. Distributed Hash Tables

Authors: Klaus Wehrle; Stefan Götz; Simon Rieche;

7. Distributed Hash Tables

Abstract

In the last few years, an increasing number of massively distributed systems with millions of participants has emerged within very short time frames. Applications, such as instant messaging, file-sharing, and content distribution have attracted countless numbers of users. For example, Skype gained more than 2.5 millions of users within twelve months, and more than 50% of Internet traffic is originated by BitTorrent. These very large and still rapidly growing systems attest to a new era for the design and deployment of distributed systems [52]. In particular, they reflect what the major challenges are today for designing and implementing distributed systems: scalability, flexibility, and instant deployment.

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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!
9
Average
Top 10%
Average
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