Universally-Optimal Distributed Exact Min-Cut
Mohsen Ghaffari, Goran Zuzic

TL;DR
This paper introduces a universally-optimal distributed algorithm for exact weighted min-cut, achieving near-optimal round complexity on all graphs and significantly simplifying prior approaches.
Contribution
It presents a new aggregation-based distributed algorithm for min-cut that is simpler, faster on structured graphs, and works within a versatile paradigm allowing virtual nodes.
Findings
Achieves $ ilde{O}(D + \sqrt{n})$ rounds on all graphs
Runs in $ ilde{O}(D)$ rounds on planar and excluded-minor graphs
Provides a deterministic near-optimal algorithm for 2-respecting min-cut
Abstract
We present a universally-optimal distributed algorithm for the exact weighted min-cut. The algorithm is guaranteed to complete in rounds on every graph, recovering the recent result of Dory, Efron, Mukhopadhyay, and Nanongkai~[STOC'21], but runs much faster on structured graphs. Specifically, the algorithm completes in rounds on (weighted) planar graphs or, more generally, any (weighted) excluded-minor family. We obtain this result by designing an aggregation-based algorithm: each node receives only an aggregate of the messages sent to it. While somewhat restrictive, recent work shows any such black-box algorithm can be simulated on any minor of the communication network. Furthermore, we observe this also allows for the addition of (a small number of) arbitrarily-connected virtual nodes to the network. We leverage these capabilities to…
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