{"title":"Online and Approximate Network Construction from Bounded Connectivity Constraints","authors":"Jesper Jansson, C. Levcopoulos, A. Lingas","doi":"10.1142/s0129054122500265","DOIUrl":null,"url":null,"abstract":"The Network Construction problem, studied by Angluin et al., Hosoda et al., and others, asks for a minimum-cost network satisfying a set of connectivity constraints which specify subsets of the vertices in the network that have to form connected subgraphs. More formally, given a set [Formula: see text] of vertices, construction costs for all possible edges between pairs of vertices from [Formula: see text], and a sequence [Formula: see text] of connectivity constraints, the objective is to find a set [Formula: see text] of edges such that each [Formula: see text] induces a connected subgraph of the graph [Formula: see text] and the total cost of [Formula: see text] is minimized. First, we study the online version where every constraint must be satisfied immediately after its arrival and edges that have already been added can never be removed. We give an [Formula: see text]-competitive and [Formula: see text]-competitive polynomial-time algorithms, where [Formula: see text] is an upper bound on the size of constraints, while [Formula: see text] denote the number of constraints and the number of vertices, respectively. On the other hand, we observe that an [Formula: see text]-competitive lower bound as well as an [Formula: see text]-competitive lower bound in the cost-uniform case are implied by the known lower bounds for unbounded constraints. For the cost-uniform case with unbounded constraints, we provide an [Formula: see text]-competitive upper bound with high probability. The latter bound is against an oblivious adversary while our other randomized competitive bounds are against an adaptive adversary. Next, we discuss a hybrid approximation method for the (offline) Network Construction problem combining an approximation algorithm of Hosoda et al. with one of Angluin et al. and an application of the hybrid method to bioinformatics. Finally, we consider a natural strengthening of the connectivity requirements in the Network Construction problem, where each constraint has to induce a subgraph (of the constructed graph) of diameter at most [Formula: see text]. Among other things, we provide a polynomial-time [Formula: see text]-approximation algorithm for the Network Construction problem with the [Formula: see text]-diameter requirements, when each constraint has at most [Formula: see text] vertices, and show the APX-completeness of this variant.","PeriodicalId":192109,"journal":{"name":"Int. J. Found. Comput. Sci.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Found. Comput. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0129054122500265","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Network Construction problem, studied by Angluin et al., Hosoda et al., and others, asks for a minimum-cost network satisfying a set of connectivity constraints which specify subsets of the vertices in the network that have to form connected subgraphs. More formally, given a set [Formula: see text] of vertices, construction costs for all possible edges between pairs of vertices from [Formula: see text], and a sequence [Formula: see text] of connectivity constraints, the objective is to find a set [Formula: see text] of edges such that each [Formula: see text] induces a connected subgraph of the graph [Formula: see text] and the total cost of [Formula: see text] is minimized. First, we study the online version where every constraint must be satisfied immediately after its arrival and edges that have already been added can never be removed. We give an [Formula: see text]-competitive and [Formula: see text]-competitive polynomial-time algorithms, where [Formula: see text] is an upper bound on the size of constraints, while [Formula: see text] denote the number of constraints and the number of vertices, respectively. On the other hand, we observe that an [Formula: see text]-competitive lower bound as well as an [Formula: see text]-competitive lower bound in the cost-uniform case are implied by the known lower bounds for unbounded constraints. For the cost-uniform case with unbounded constraints, we provide an [Formula: see text]-competitive upper bound with high probability. The latter bound is against an oblivious adversary while our other randomized competitive bounds are against an adaptive adversary. Next, we discuss a hybrid approximation method for the (offline) Network Construction problem combining an approximation algorithm of Hosoda et al. with one of Angluin et al. and an application of the hybrid method to bioinformatics. Finally, we consider a natural strengthening of the connectivity requirements in the Network Construction problem, where each constraint has to induce a subgraph (of the constructed graph) of diameter at most [Formula: see text]. Among other things, we provide a polynomial-time [Formula: see text]-approximation algorithm for the Network Construction problem with the [Formula: see text]-diameter requirements, when each constraint has at most [Formula: see text] vertices, and show the APX-completeness of this variant.
Angluin等人、Hosoda等人研究的网络构造问题(Network Construction problem)要求一个最小代价的网络满足一组连接约束,这些连接约束规定了网络中必须形成连通子图的顶点子集。更正式地说,给定一组[公式:见文]的顶点,在[公式:见文]的顶点对之间的所有可能的边的构建成本,以及连接约束的序列[公式:见文],目标是找到一组[公式:见文]的边,这样每个[公式:见文]都能引出图[公式:见文]的连通子图,并且[公式:见文]的总成本最小。首先,我们研究了在线版本,其中每个约束必须在到达后立即得到满足,并且已经添加的边永远不能删除。我们给出了[公式:见文]-竞争和[公式:见文]-竞争多项式时间算法,其中[公式:见文]是约束大小的上界,而[公式:见文]分别表示约束的数量和顶点的数量。另一方面,我们观察到[公式:见文]竞争下界和[公式:见文]成本均匀情况下的竞争下界是由无界约束的已知下界隐含的。对于具有无界约束的成本一致情况,我们提供了一个[公式:见文本]-高概率竞争上界。后一个界限是针对无意识对手的,而另一个随机竞争界限是针对适应性对手的。接下来,我们将Hosoda等人的近似算法与Angluin等人的近似算法相结合,讨论了(离线)网络构建问题的混合近似方法,以及该混合方法在生物信息学中的应用。最后,我们考虑网络构造问题中连通性要求的自然强化,其中每个约束必须诱导(构造图的)最大直径的子图[公式:见文本]。在其他方面,我们提供了一个多项式时间[公式:见文本]的网络建设问题的近似算法[公式:见文本]-直径要求,当每个约束有最多[公式:见文本]顶点时,并显示了这种变体的apx -完备性。