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تسجيل مستخدم جديدBeating the Folklore Algorithm for Dynamic Matching
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The maximum matching problem in dynamic graphs subject to edge updates (insertions and deletions) has received much attention over the last few years; a multitude of approximation/time tradeoffs were obtained, improving upon the folklore algorithm, which maintains a maximal (and hence $2$-approximate) matching in $O(n)$ worst-case update time in $n$-node graphs. We present the first deterministic algorithm which outperforms the folklore algorithm in terms of {em both} approximation ratio and worst-case update time. Specifically, we give a $(2-Omega(1))$-approximate algorithm with $O(sqrt{n}sqrt[8]{m})=O(n^{3/4})$ worst-case update time in $n$-node, $m$-edge graphs. For sufficiently small constant $epsilon>0$, no deterministic $(2+epsilon)$-approximate algorithm with worst-case update time $O(n^{0.99})$ was known. Our second result is the first deterministic $(2+epsilon)$-approximate (weighted) matching algorithm with $O_epsilon(1)cdot O(sqrt[4]{m}) = O_epsilon(1)cdot O(sqrt{n})$ worst-case update time.
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