Distributed Strong Diameter Network Decomposition
Abstract
For a pair of positive parameters , a partition of the vertex set of an -vertex graph into disjoint clusters of diameter at most each is called a network decomposition, if the supergraph , obtained by contracting each of the clusters of , can be properly -colored. The decomposition is said to be strong (resp., weak) if each of the clusters has strong (resp., weak) diameter at most , i.e., if for every cluster and every two vertices , the distance between them in the induced graph of (resp., in ) is at most . Network decomposition is a powerful construct, very useful in distributed computing and beyond. It was shown by Awerbuch \etal \cite{AGLP89} and Panconesi and Srinivasan \cite{PS92}, that strong network decompositions can be computed in distributed time. Linial and Saks \cite{LS93} devised an ingenious randomized algorithm that constructs {\em weak} network decompositions in time. It was however open till now if {\em strong} network decompositions with both parameters can be constructed in distributed time. In this paper we answer this long-standing open question in the affirmative, and show that strong network decompositions can be computed in time. We also present a tradeoff between parameters of our network decomposition. Our work is inspired by and relies on the "shifted shortest path approach", due to Blelloch \etal \cite{BGKMPT11}, and Miller \etal \cite{MPX13}. These authors developed this approach for PRAM algorithms for padded partitions. We adapt their approach to network decompositions in the distributed model of computation.
Keywords
Cite
@article{arxiv.1602.05437,
title = {Distributed Strong Diameter Network Decomposition},
author = {Michael Elkin and Ofer Neiman},
journal= {arXiv preprint arXiv:1602.05437},
year = {2016}
}