{"title":"一个简单的图重建算法","authors":"Claire Mathieu, Hang Zhou","doi":"10.1002/rsa.21143","DOIUrl":null,"url":null,"abstract":"How efficiently can we find an unknown graph using distance queries between its vertices? We assume that the unknown graph is connected, unweighted, and has bounded degree. The goal is to find every edge in the graph. This problem admits a reconstruction algorithm based on multi‐phase Voronoi‐cell decomposition and using Õ(n3/2)$$ \\overset{\\widetilde }{O}\\left({n}^{3/2}\\right) $$ distance queries. In our work, we analyze a simple reconstruction algorithm. We show that, on random Δ$$ \\Delta $$ ‐regular graphs, our algorithm uses Õ(n)$$ \\overset{\\widetilde }{O}(n) $$ distance queries. As by‐products, with high probability, we can reconstruct those graphs using log2n$$ {\\log}^2n $$ queries to an all‐distances oracle or Õ(n)$$ \\overset{\\widetilde }{O}(n) $$ queries to a betweenness oracle, and we bound the metric dimension of those graphs by log2n$$ {\\log}^2n $$ . Our reconstruction algorithm has a very simple structure, and is highly parallelizable. On general graphs of bounded degree, our reconstruction algorithm has subquadratic query complexity.","PeriodicalId":54523,"journal":{"name":"Random Structures & Algorithms","volume":"60 1","pages":"512 - 532"},"PeriodicalIF":0.9000,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A simple algorithm for graph reconstruction\",\"authors\":\"Claire Mathieu, Hang Zhou\",\"doi\":\"10.1002/rsa.21143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"How efficiently can we find an unknown graph using distance queries between its vertices? We assume that the unknown graph is connected, unweighted, and has bounded degree. The goal is to find every edge in the graph. This problem admits a reconstruction algorithm based on multi‐phase Voronoi‐cell decomposition and using Õ(n3/2)$$ \\\\overset{\\\\widetilde }{O}\\\\left({n}^{3/2}\\\\right) $$ distance queries. In our work, we analyze a simple reconstruction algorithm. We show that, on random Δ$$ \\\\Delta $$ ‐regular graphs, our algorithm uses Õ(n)$$ \\\\overset{\\\\widetilde }{O}(n) $$ distance queries. As by‐products, with high probability, we can reconstruct those graphs using log2n$$ {\\\\log}^2n $$ queries to an all‐distances oracle or Õ(n)$$ \\\\overset{\\\\widetilde }{O}(n) $$ queries to a betweenness oracle, and we bound the metric dimension of those graphs by log2n$$ {\\\\log}^2n $$ . Our reconstruction algorithm has a very simple structure, and is highly parallelizable. On general graphs of bounded degree, our reconstruction algorithm has subquadratic query complexity.\",\"PeriodicalId\":54523,\"journal\":{\"name\":\"Random Structures & Algorithms\",\"volume\":\"60 1\",\"pages\":\"512 - 532\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2021-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Random Structures & Algorithms\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1002/rsa.21143\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Random Structures & Algorithms","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1002/rsa.21143","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
How efficiently can we find an unknown graph using distance queries between its vertices? We assume that the unknown graph is connected, unweighted, and has bounded degree. The goal is to find every edge in the graph. This problem admits a reconstruction algorithm based on multi‐phase Voronoi‐cell decomposition and using Õ(n3/2)$$ \overset{\widetilde }{O}\left({n}^{3/2}\right) $$ distance queries. In our work, we analyze a simple reconstruction algorithm. We show that, on random Δ$$ \Delta $$ ‐regular graphs, our algorithm uses Õ(n)$$ \overset{\widetilde }{O}(n) $$ distance queries. As by‐products, with high probability, we can reconstruct those graphs using log2n$$ {\log}^2n $$ queries to an all‐distances oracle or Õ(n)$$ \overset{\widetilde }{O}(n) $$ queries to a betweenness oracle, and we bound the metric dimension of those graphs by log2n$$ {\log}^2n $$ . Our reconstruction algorithm has a very simple structure, and is highly parallelizable. On general graphs of bounded degree, our reconstruction algorithm has subquadratic query complexity.
期刊介绍:
It is the aim of this journal to meet two main objectives: to cover the latest research on discrete random structures, and to present applications of such research to problems in combinatorics and computer science. The goal is to provide a natural home for a significant body of current research, and a useful forum for ideas on future studies in randomness.
Results concerning random graphs, hypergraphs, matroids, trees, mappings, permutations, matrices, sets and orders, as well as stochastic graph processes and networks are presented with particular emphasis on the use of probabilistic methods in combinatorics as developed by Paul Erdõs. The journal focuses on probabilistic algorithms, average case analysis of deterministic algorithms, and applications of probabilistic methods to cryptography, data structures, searching and sorting. The journal also devotes space to such areas of probability theory as percolation, random walks and combinatorial aspects of probability.