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Durham Research Online
Part of book or chapter of book . 2019 . Peer-reviewed
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https://doi.org/10.1109/ipdps....
Article . 2019 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
DBLP
Conference object . 2022
Data sources: DBLP
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Tight & Simple Load Balancing

Authors: Petra Berenbrink; Tom Friedetzky; Dominik Kaaser; Peter Kling;

Tight & Simple Load Balancing

Abstract

We consider the following load balancing process for m tokens distributed arbitrarily among n nodes connected by a complete graph. In each time step a pair of nodes is selected uniformly at random. Let l_1 and l_2 be their respective number of tokens. The two nodes exchange tokens such that they have ⌈(l_1 + l_2)/2⌉ and ⌈(l_1 + l_2)/2⌉ tokens, respectively. We provide a simple analysis showing that this process reaches almost perfect balance within O(n log n + n log Δ) steps with high probability, where Δ is the maximal initial load difference between any two nodes. This bound is asymptotically tight.

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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!
4
Average
Average
Average
Green