Near-Optimal Deterministic Network Decomposition and Ruling Set, and Improved MIS
Mohsen Ghaffari, Christoph Grunau

TL;DR
This paper presents near-optimal deterministic algorithms for fundamental distributed graph problems, significantly improving round complexities and nearly matching theoretical lower bounds for network decomposition, ruling sets, and MIS.
Contribution
It introduces new deterministic algorithms that nearly settle the round complexity for network decomposition, ruling sets, and MIS, improving prior bounds and breaking longstanding barriers.
Findings
Network decomposition algorithm runs in ~O(log^2 n) rounds, near the theoretical lower bound.
Deterministic ruling set algorithm computes an O(log log n) ruling set in ~O(log n) rounds.
MIS algorithm achieves ~O(log^(5/3) n) rounds, breaking the previous log-squared barrier.
Abstract
This paper improves and in two cases nearly settles, up to logarithmically lower-order factors, the deterministic complexity of some of the most central problems in distributed graph algorithms, which have been studied for over three decades: Near-Optimal Network Decomposition: We present a deterministic distributed algorithm that computes a network decomposition in approximately O(log^2 n) rounds, with O(log n) diameter and O(log n) colors. This round complexity is near-optimal in the following sense: even given an ideal network decomposition, using it (in the standard way) requires round complexity equal to the product of diameter and number of colors, which is known to be approximately Omega(log^2 n). This near-optimality is remarkable, considering the rarity of optimal deterministic distributed algorithms and that for network decomposition, the first polylogarithmic-round…
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Taxonomy
TopicsAdvanced Queuing Theory Analysis
