Smoothed Analysis of Balancing Networks

Computer Science – Data Structures and Algorithms

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

26 pages, to appear in Random Structures and Algorithms

Scientific paper

In a 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 affects 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). We start with an arbitrary assignment of balancer directions and then flip each assignment with probability $\alpha$ independently. For a large class of balancing networks our result implies that after $\Oh(\log n)$ rounds the discrepancy is $\Oh( (1/2-\alpha) \log n + \log \log n)$ with high probability. This matches and generalizes known upper bounds for $\alpha=0$ and $\alpha=1/2$. We also show that a natural network matches the upper bound for any $\alpha$.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Smoothed Analysis of Balancing Networks does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Smoothed Analysis of Balancing Networks, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Smoothed Analysis of Balancing Networks will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-29562

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.