{"title":"Bridging the Gap Between Tree and Connectivity Augmentation: Unified and Stronger Approaches","authors":"Federica Cecchetto, Vera Traub, Rico Zenklusen","doi":"10.1137/21m1430601","DOIUrl":null,"url":null,"abstract":"We consider the connectivity augmentation problem (CAP), a classical problem in the area of survivable network design. It is about increasing the edge-connectivity of a graph by one unit in the cheapest possible way. More precisely, given a -edge-connected graph and a set of extra edges, the task is to find a minimum cardinality subset of extra edges whose addition to makes the graph -edge-connected. If is odd, the problem is known to reduce to the tree augmentation problem (TAP)—i.e., is a spanning tree—for which significant progress has been achieved recently, leading to approximation factors below 1.5 (the current best factor is 1.458). However, advances on TAP have not carried over to CAP so far. Indeed, only very recently, Byrka, Grandoni, and Ameli [Proceedings of the 52nd ACM Symposium on Theory of Computing, 2020, pp. 815–825] managed to obtain the first approximation factor below 2 for CAP by presenting a 1.91-approximation algorithm based on a method that is disjoint from recent advances for TAP. We first bridge the gap between TAP and CAP by presenting techniques that allow for leveraging insights and methods from TAP to approach CAP. We then introduce a new way to get approximation factors below 1.5, based on a new analysis technique. Through these ingredients, we obtain a 1.393-approximation algorithm for CAP, and therefore also for TAP. This leads to the current best approximation result for both problems in a unified way, by significantly improving on the abovementioned 1.91-approximation for CAP and also the previously best approximation factor of 1.458 for TAP by Grandoni, Kalaitzis, and Zenklusen [Proceedings of the 50th ACM Symposium on Theory of Computing, 2018, pp. 632–645]. Additionally, a feature we inherit from recent TAP advances is that our approach can deal with the weighted setting when the ratio of the largest to smallest cost on extra links is bounded, in which case we obtain approximation factors below 1.5.","PeriodicalId":49532,"journal":{"name":"SIAM Journal on Computing","volume":"115 1","pages":"0"},"PeriodicalIF":1.2000,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SIAM Journal on Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1137/21m1430601","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
We consider the connectivity augmentation problem (CAP), a classical problem in the area of survivable network design. It is about increasing the edge-connectivity of a graph by one unit in the cheapest possible way. More precisely, given a -edge-connected graph and a set of extra edges, the task is to find a minimum cardinality subset of extra edges whose addition to makes the graph -edge-connected. If is odd, the problem is known to reduce to the tree augmentation problem (TAP)—i.e., is a spanning tree—for which significant progress has been achieved recently, leading to approximation factors below 1.5 (the current best factor is 1.458). However, advances on TAP have not carried over to CAP so far. Indeed, only very recently, Byrka, Grandoni, and Ameli [Proceedings of the 52nd ACM Symposium on Theory of Computing, 2020, pp. 815–825] managed to obtain the first approximation factor below 2 for CAP by presenting a 1.91-approximation algorithm based on a method that is disjoint from recent advances for TAP. We first bridge the gap between TAP and CAP by presenting techniques that allow for leveraging insights and methods from TAP to approach CAP. We then introduce a new way to get approximation factors below 1.5, based on a new analysis technique. Through these ingredients, we obtain a 1.393-approximation algorithm for CAP, and therefore also for TAP. This leads to the current best approximation result for both problems in a unified way, by significantly improving on the abovementioned 1.91-approximation for CAP and also the previously best approximation factor of 1.458 for TAP by Grandoni, Kalaitzis, and Zenklusen [Proceedings of the 50th ACM Symposium on Theory of Computing, 2018, pp. 632–645]. Additionally, a feature we inherit from recent TAP advances is that our approach can deal with the weighted setting when the ratio of the largest to smallest cost on extra links is bounded, in which case we obtain approximation factors below 1.5.
期刊介绍:
The SIAM Journal on Computing aims to provide coverage of the most significant work going on in the mathematical and formal aspects of computer science and nonnumerical computing. Submissions must be clearly written and make a significant technical contribution. Topics include but are not limited to analysis and design of algorithms, algorithmic game theory, data structures, computational complexity, computational algebra, computational aspects of combinatorics and graph theory, computational biology, computational geometry, computational robotics, the mathematical aspects of programming languages, artificial intelligence, computational learning, databases, information retrieval, cryptography, networks, distributed computing, parallel algorithms, and computer architecture.