{"title":"Almost Shortest Paths with Near-Additive Error in Weighted Graphs","authors":"Michael Elkin, Yuval Gitlitz, Ofer Neiman","doi":"10.4230/LIPIcs.SWAT.2022.23","DOIUrl":null,"url":null,"abstract":"Let $G=(V,E,w)$ be a weighted undirected graph with $n$ vertices and $m$ edges, and fix a set of $s$ sources $S\\subseteq V$. We study the problem of computing {\\em almost shortest paths} (ASP) for all pairs in $S \\times V$ in both classical centralized and parallel (PRAM) models of computation. Consider the regime of multiplicative approximation of $1+\\epsilon$, for an arbitrarily small constant $\\epsilon > 0$ . In this regime existing centralized algorithms require $\\Omega(\\min\\{|E|s,n^\\omega\\})$ time, where $\\omega < 2.372$ is the matrix multiplication exponent. Existing PRAM algorithms with polylogarithmic depth (aka time) require work $\\Omega(\\min\\{|E|s,n^\\omega\\})$. \nOur centralized algorithm has running time $O((m+ ns)n^\\rho)$, and its PRAM counterpart has polylogarithmic depth and work $O((m + ns)n^\\rho)$, for an arbitrarily small constant $\\rho > 0$. For a pair $(s,v) \\in S\\times V$, it provides a path of length $\\hat{d}(s,v)$ that satisfies $\\hat{d}(s,v) \\le (1+\\epsilon)d_G(s,v) + \\beta \\cdot W(s,v)$, where $W(s,v)$ is the weight of the heaviest edge on some shortest $s-v$ path. Hence our additive term depends linearly on a {\\em local} maximum edge weight, as opposed to the global maximum edge weight in previous works. Finally, our $\\beta = (1/\\rho)^{O(1/\\rho)}$. \nWe also extend a centralized algorithm of Dor et al. \\cite{DHZ00}. For a parameter $\\kappa = 1,2,\\ldots$, this algorithm provides for {\\em unweighted} graphs a purely additive approximation of $2(\\kappa -1)$ for {\\em all pairs shortest paths} (APASP) in time $\\tilde{O}(n^{2+1/\\kappa})$. Within the same running time, our algorithm for {\\em weighted} graphs provides a purely additive error of $2(\\kappa - 1) W(u,v)$, for every vertex pair $(u,v) \\in {V \\choose 2}$, with $W(u,v)$ defined as above. \nOn the way to these results we devise a suit of novel constructions of spanners, emulators and hopsets.","PeriodicalId":447445,"journal":{"name":"Scandinavian Workshop on Algorithm Theory","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scandinavian Workshop on Algorithm Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4230/LIPIcs.SWAT.2022.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
Let $G=(V,E,w)$ be a weighted undirected graph with $n$ vertices and $m$ edges, and fix a set of $s$ sources $S\subseteq V$. We study the problem of computing {\em almost shortest paths} (ASP) for all pairs in $S \times V$ in both classical centralized and parallel (PRAM) models of computation. Consider the regime of multiplicative approximation of $1+\epsilon$, for an arbitrarily small constant $\epsilon > 0$ . In this regime existing centralized algorithms require $\Omega(\min\{|E|s,n^\omega\})$ time, where $\omega < 2.372$ is the matrix multiplication exponent. Existing PRAM algorithms with polylogarithmic depth (aka time) require work $\Omega(\min\{|E|s,n^\omega\})$.
Our centralized algorithm has running time $O((m+ ns)n^\rho)$, and its PRAM counterpart has polylogarithmic depth and work $O((m + ns)n^\rho)$, for an arbitrarily small constant $\rho > 0$. For a pair $(s,v) \in S\times V$, it provides a path of length $\hat{d}(s,v)$ that satisfies $\hat{d}(s,v) \le (1+\epsilon)d_G(s,v) + \beta \cdot W(s,v)$, where $W(s,v)$ is the weight of the heaviest edge on some shortest $s-v$ path. Hence our additive term depends linearly on a {\em local} maximum edge weight, as opposed to the global maximum edge weight in previous works. Finally, our $\beta = (1/\rho)^{O(1/\rho)}$.
We also extend a centralized algorithm of Dor et al. \cite{DHZ00}. For a parameter $\kappa = 1,2,\ldots$, this algorithm provides for {\em unweighted} graphs a purely additive approximation of $2(\kappa -1)$ for {\em all pairs shortest paths} (APASP) in time $\tilde{O}(n^{2+1/\kappa})$. Within the same running time, our algorithm for {\em weighted} graphs provides a purely additive error of $2(\kappa - 1) W(u,v)$, for every vertex pair $(u,v) \in {V \choose 2}$, with $W(u,v)$ defined as above.
On the way to these results we devise a suit of novel constructions of spanners, emulators and hopsets.