← 研踪 PaperTrailarXiv:2611.12827 · v1
Flows in High Degree Places: Sublinear Spanning Tree Congestion
高度数场所中的流:次线性生成树拥塞
首次提交 2026-11-10 02:27
版本更新 2026-11-10 02:27
雷达观测 2026-11-10 15:22
摘要
The congestion of a spanning tree of graph is the maximum congestion of an edge of if each edge of is routed on . Prior work showed that obtaining a minimum congestion spanning tree is NP-hard to approximate within , yet the only known approximation algorithm is a trivial -approximation from returning any spanning tree of the graph. We give a simple poly-time -approximation for minimum congestion spanning tree on -vertex graphs. We obtain this result via a -approximation, where is the number of edges. Our algorithm is based on a new \textit{flow-or-degree decomposition} which deletes a small number of edges so that each remaining component either has low degree or admits a low congestion flow. We also show that, assuming the Small Set Expansion Hypothesis, it is NP-hard to -approximate this problem, even on graphs of constant maximum degree.
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v1 · 2026-11-10 02:27 · 最新观测版本
Flows in High Degree Places: Sublinear Spanning Tree Congestion
The congestion of a spanning tree of graph is the maximum congestion of an edge of if each edge of is routed on . Prior work showed that obtaining a minimum congestion spanning tree is NP-hard to approximate within , yet the only known approximation algorithm is a trivial -approximation from returning any spanning tree of the graph. We give a simple poly-time -approximation for minimum congestion spanning tree on -vertex graphs. We obtain this result via a -approximation, where is the number of edges. Our algorithm is based on a new \textit{flow-or-degree decomposition} which deletes a small number of edges so that each remaining component either has low degree or admits a low congestion flow. We also show that, assuming the Small Set Expansion Hypothesis, it is NP-hard to -approximate this problem, even on graphs of constant maximum degree.
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