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Local-on-average distributed tasks

Published: 10 January 2016 Publication History

Abstract

A distributed task is local if its time complexity is (nearly) constant, otherwise it is global. Unfortunately, local tasks are relatively scarce, and most distributed tasks require time at least logarithmic in the network size (and often higher than that). In a dynamic setting, i.e., when the network undergoes repeated and frequent topological changes, such as vertex and edge insertions and deletions, it is desirable to be able to perform a local update procedure around the modified part of the network, rather than running a static global algorithm from scratch following each change.
This paper makes a step towards establishing the hypothesis that many (statically) non-local distributed tasks are local-on-average in the dynamic setting, namely, their amortized time complexity is O(log* n).
Towards establishing the plausibility of this hypothesis, we propose a strategy for transforming static O(polylog(n)) time algorithms into dynamic O(log* n) amortized time update procedures. We then demonstrate the usefulness of our strategy by applying it to several fundamental problems whose static time complexity is logarithmic, including forest-decomposition, edge-orientation and coloring sparse graphs, and show that their amortized time complexity in the dynamic setting is indeed O(log* n).

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cover image ACM Conferences
SODA '16: Proceedings of the twenty-seventh annual ACM-SIAM symposium on Discrete algorithms
January 2016
2114 pages
ISBN:9781611974331

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Published: 10 January 2016

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SODA '16: Symposium on Discrete Algorithms
January 10 - 12, 2016
Virginia, Arlington

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