{"title":"顶点稀疏化和抽象舍入算法","authors":"M. Charikar, F. Leighton, Shi Li, Ankur Moitra","doi":"10.1109/FOCS.2010.32","DOIUrl":null,"url":null,"abstract":"The notion of vertex sparsification (in particular cut-sparsification) is introduced in (Moitra, 2009), where it was shown that for any graph $G = (V, E)$ and any subset of $k$ terminals $K \\subset V$, there is a polynomial time algorithm to construct a graph $H = (K, E_H)$ \\emph{on just the terminal set} so that simultaneously for all cuts $(A, K-A)$, the value of the minimum cut in $G$ separating $A$ from $K -A$ is approximately the same as the value of the corresponding cut in $H$. Then approximation algorithms can be run directly on $H$ as a proxy for running on $G$. We give the first super-constant lower bounds for how well a cut-sparsifier $H$ can simultaneously approximate all minimum cuts in $G$. %In fact, we prove that in general we cannot hope for approximation factors better than We prove a lower bound of $\\Omega(\\log^{1/4} k)$ – this is polynomially-related to the known upper bound of $O(\\log k/\\log \\log k)$. Independently, a similar lower bound is given in (Makarychev, Makarychev, 2010). This is an exponential improvement on the $\\Omega(\\log \\log k)$ bound given in (Leighton, Moitra, 2010) which in fact was for a stronger vertex sparsification guarantee, and did not apply to cut sparsifiers. Despite this negative result, we show that for many natural optimization problems, we do not need to incur a multiplicative penalty for our reduction. Roughly, we show that any rounding algorithm which also works for the $0$-extension relaxation can be used to construct good vertex-sparsifiers for which the optimization problem is easy. Using this, we obtain optimal $O(\\log k)$-competitive Steiner oblivious routing schemes, which generalize the results in (Raecke, 2008). We also demonstrate that for a wide range of graph packing problems (which includes maximum concurrent flow, maximum multiflow and multicast routing, among others, as a special case), the integrality gap of the linear program is always at most $O(\\log k)$ times the integrality gap restricted to trees. Lastly, we use our ideas to give an efficient construction for vertex-sparsifiers that match the current best existential results – this was previously open. Our algorithm makes novel use of Earth-mover constraints.","PeriodicalId":228365,"journal":{"name":"2010 IEEE 51st Annual Symposium on Foundations of Computer Science","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"58","resultStr":"{\"title\":\"Vertex Sparsifiers and Abstract Rounding Algorithms\",\"authors\":\"M. Charikar, F. Leighton, Shi Li, Ankur Moitra\",\"doi\":\"10.1109/FOCS.2010.32\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The notion of vertex sparsification (in particular cut-sparsification) is introduced in (Moitra, 2009), where it was shown that for any graph $G = (V, E)$ and any subset of $k$ terminals $K \\\\subset V$, there is a polynomial time algorithm to construct a graph $H = (K, E_H)$ \\\\emph{on just the terminal set} so that simultaneously for all cuts $(A, K-A)$, the value of the minimum cut in $G$ separating $A$ from $K -A$ is approximately the same as the value of the corresponding cut in $H$. Then approximation algorithms can be run directly on $H$ as a proxy for running on $G$. We give the first super-constant lower bounds for how well a cut-sparsifier $H$ can simultaneously approximate all minimum cuts in $G$. %In fact, we prove that in general we cannot hope for approximation factors better than We prove a lower bound of $\\\\Omega(\\\\log^{1/4} k)$ – this is polynomially-related to the known upper bound of $O(\\\\log k/\\\\log \\\\log k)$. Independently, a similar lower bound is given in (Makarychev, Makarychev, 2010). This is an exponential improvement on the $\\\\Omega(\\\\log \\\\log k)$ bound given in (Leighton, Moitra, 2010) which in fact was for a stronger vertex sparsification guarantee, and did not apply to cut sparsifiers. Despite this negative result, we show that for many natural optimization problems, we do not need to incur a multiplicative penalty for our reduction. Roughly, we show that any rounding algorithm which also works for the $0$-extension relaxation can be used to construct good vertex-sparsifiers for which the optimization problem is easy. Using this, we obtain optimal $O(\\\\log k)$-competitive Steiner oblivious routing schemes, which generalize the results in (Raecke, 2008). We also demonstrate that for a wide range of graph packing problems (which includes maximum concurrent flow, maximum multiflow and multicast routing, among others, as a special case), the integrality gap of the linear program is always at most $O(\\\\log k)$ times the integrality gap restricted to trees. Lastly, we use our ideas to give an efficient construction for vertex-sparsifiers that match the current best existential results – this was previously open. 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引用次数: 58
摘要
在(Moitra, 2009)中引入了顶点稀疏化(特别是切点稀疏化)的概念,其中证明了对于任何图$G = (V, E)$和$k$终端$K \subset V$的任何子集,存在一个多项式时间算法来在\emph{终端集上}构建图$H = (K, E_H)$,以便同时对于所有切点$(A, K-A)$,$G$中分离$A$和$K -A$的最小切割量的值与$H$中相应的切割量的值大致相同。然后,近似算法可以直接在$H$上运行,作为在$G$上运行的代理。我们给出了cut- sparfier $H$同时近似$G$中所有最小cut的第一个超常数下界。 %In fact, we prove that in general we cannot hope for approximation factors better than We prove a lower bound of $\Omega(\log^{1/4} k)$ – this is polynomially-related to the known upper bound of $O(\log k/\log \log k)$. Independently, a similar lower bound is given in (Makarychev, Makarychev, 2010). This is an exponential improvement on the $\Omega(\log \log k)$ bound given in (Leighton, Moitra, 2010) which in fact was for a stronger vertex sparsification guarantee, and did not apply to cut sparsifiers. Despite this negative result, we show that for many natural optimization problems, we do not need to incur a multiplicative penalty for our reduction. Roughly, we show that any rounding algorithm which also works for the $0$-extension relaxation can be used to construct good vertex-sparsifiers for which the optimization problem is easy. Using this, we obtain optimal $O(\log k)$-competitive Steiner oblivious routing schemes, which generalize the results in (Raecke, 2008). We also demonstrate that for a wide range of graph packing problems (which includes maximum concurrent flow, maximum multiflow and multicast routing, among others, as a special case), the integrality gap of the linear program is always at most $O(\log k)$ times the integrality gap restricted to trees. Lastly, we use our ideas to give an efficient construction for vertex-sparsifiers that match the current best existential results – this was previously open. Our algorithm makes novel use of Earth-mover constraints.
Vertex Sparsifiers and Abstract Rounding Algorithms
The notion of vertex sparsification (in particular cut-sparsification) is introduced in (Moitra, 2009), where it was shown that for any graph $G = (V, E)$ and any subset of $k$ terminals $K \subset V$, there is a polynomial time algorithm to construct a graph $H = (K, E_H)$ \emph{on just the terminal set} so that simultaneously for all cuts $(A, K-A)$, the value of the minimum cut in $G$ separating $A$ from $K -A$ is approximately the same as the value of the corresponding cut in $H$. Then approximation algorithms can be run directly on $H$ as a proxy for running on $G$. We give the first super-constant lower bounds for how well a cut-sparsifier $H$ can simultaneously approximate all minimum cuts in $G$. %In fact, we prove that in general we cannot hope for approximation factors better than We prove a lower bound of $\Omega(\log^{1/4} k)$ – this is polynomially-related to the known upper bound of $O(\log k/\log \log k)$. Independently, a similar lower bound is given in (Makarychev, Makarychev, 2010). This is an exponential improvement on the $\Omega(\log \log k)$ bound given in (Leighton, Moitra, 2010) which in fact was for a stronger vertex sparsification guarantee, and did not apply to cut sparsifiers. Despite this negative result, we show that for many natural optimization problems, we do not need to incur a multiplicative penalty for our reduction. Roughly, we show that any rounding algorithm which also works for the $0$-extension relaxation can be used to construct good vertex-sparsifiers for which the optimization problem is easy. Using this, we obtain optimal $O(\log k)$-competitive Steiner oblivious routing schemes, which generalize the results in (Raecke, 2008). We also demonstrate that for a wide range of graph packing problems (which includes maximum concurrent flow, maximum multiflow and multicast routing, among others, as a special case), the integrality gap of the linear program is always at most $O(\log k)$ times the integrality gap restricted to trees. Lastly, we use our ideas to give an efficient construction for vertex-sparsifiers that match the current best existential results – this was previously open. Our algorithm makes novel use of Earth-mover constraints.