Smoothed analysis of balancing networks

Tobias Friedrich, Thomas Sauerwald, Dan Vilenchik

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


In a load balancing network each processor has an initial collection of unit-size jobs, tokens, and in each round, pairs of processors connected by balancers split their load as evenly as possible. An excess token (if any) is placed according to some predefined rule. As it turns out, this rule crucially effects the performance of the network. In this work we propose a model that studies this effect. We suggest a model bridging the uniformly-random assignment rule, and the arbitrary one (in the spirit of smoothed-analysis) by starting from an arbitrary assignment of balancer directions, then flipping each assignment with probability α independently. For a large class of balancing networks our result implies that after O (log n)rounds the discrepancy is whp . O((1/2-α)log n + log log n)This matches and generalizes the known bounds for α= 0 and α= 1/2.

Original languageEnglish
Title of host publicationAutomata, Languages and Programming - 36th International Colloquium, ICALP 2009, Proceedings
Number of pages12
EditionPART 2
StatePublished - 12 Nov 2009
Externally publishedYes
Event36th International Colloquium on Automata, Languages and Programming, ICALP 2009 - Rhodes, Greece
Duration: 5 Jul 200912 Jul 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5556 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference36th International Colloquium on Automata, Languages and Programming, ICALP 2009

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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