Poly-logarithmic Approximation for Maximum Node Disjoint Paths with Constant Congestion

We consider the approximability of the maximum edge-disjoint paths problem (MEDP) in undirected graphs, and in particular, the integrality gap of the natural multicommodity flow based relaxation for it. The integrality gap is known to be \(\Omega(\sqrt{n})\) even for planar graphs [11] due to a simple topological obstruction and a major focus, following earlier work [14], has been understanding the gap if some constant congestion is allowed. In planar graphs the integrality gap is O(1) with congestion 2 [19,5]. In general graphs, recent work has shown the gap to be O(polylog(n)) [8,9] with congestion 2. Moreover, the gap is Ω(logΩ(c) n) in general graphs with congestion c for any constant c ≥ 1 [1].It is natural to ask for which classes of graphs does a constant-factor constant-congestion property hold. It is easy to deduce that for given constant bounds on the approximation and congestion, the class of “nice” graphs is minor-closed. Is the converse true? Does every proper minor-closed family of graphs exhibit a constant-factor constant-congestion bound relative to the LP relaxation? We conjecture that the answer is yes. One stumbling block has been that such bounds were not known for bounded treewidth graphs (or even treewidth 3). In this paper we give a polytime algorithm which takes a fractional routing solution in a graph of bounded treewidth and is able to integrally route a constant fraction of the LP solution’s value. Note that we do not incur any edge congestion. Previously this was not known even for series parallel graphs which have treewidth 2. The algorithm is based on a more general argument that applies to k-sums of graphs in some graph family, as long as the graph family has a constant-factor constant-congestion bound. We then use this to show that such bounds hold for the class of k-sums of bounded genus graphs.KeywordsPlanar GraphTree DecompositionGraph FamilyDisjoint Path ProblemSeries Parallel GraphThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Disjoint paths and connected subgraphs for H-free graphs

Many fundamental problems in the area of distributed systems such as security, reliable routing, network survivability and broadening available bandwidth can be addressed through the use of disjoint paths between communication endpoints. Therefore, distributed solutions to the disjoint paths problem are of crucial importance to these fundamental problems. Disjoint paths naturally exist in traditional networks; however, these networks provide no guarantees regarding the presence and the number of available disjoint paths. On the other hand, network topologies structured based on Caley graphs such as hypercube, star networks and their variations possess many desirable properties related to disjoint paths. Therefore, it is anticipated that backbones of future networks will be structured following some Caley graph topologies. In this paper, we present a simple novel stabilizing and inherently stabilizing algorithm to route messages over all node-disjoint paths of optimal length from one non-faulty process to another in at most n+1 rounds in an n-dimensional hypercube network in the presence of crash failures. The proposed algorithm can tolerate up to 2n-⌈log (n+1)⌉ process/link failures in the network and a maximum of ⌊(L-2)/3⌋ process/link failures on each disjoint path, where L is the number of processes on a disjoint path and the distance between any two failed processes/links is at least three. The proposed algorithm tolerates a large number of process and link failures, while delivering all n messages over optimal-length disjoint paths in the presence of maximum permissible process/link failures on each path. This is achieved by a simple uniform distributed algorithm using only local knowledge of failure locations.

A new polynomial time algorithm is presented for finding two vertex-disjoint paths between two specified pairs of vertices on an undirected graph. An application of the two disjoint path algorithm to the automatic wire routing is also discussed.

A software package of algorithms and heuristics for disjoint paths in Planar Networks

Given a source node and a node set, the node-to-set disjoint paths problem is to find disjoint paths from the source node to all nodes from the node set. In this paper, we propose an improved algorithm for the node-to-set disjoint paths problem on bi-rotator graphs. Our result improves the complexity of previous result from O(n5) to O(n3logn), where n is the dimension of the input graph.

Automation production systems and computer integrated manufacturing: Mikell P. Groover

In this paper we revisit the classical Edge Disjoint Paths (EDP) problem, where one is given an undirected graph G and a set of terminal pairs P and asks whether G contains a set of pairwise edge-disjoint paths connecting every terminal pair in P. Our focus lies on structural parameterizations for the problem that allow for efficient (polynomial-time or fpt) algorithms. As our first result, we answer an open question stated in Fleszar, Mnich, and Spoerhase (2016), by showing that the problem can be solved in polynomial time if the input graph has a feedback vertex set of size one. We also show that EDP parameterized by the treewidth and the maximum degree of the input graph is fixed-parameter tractable. Having developed two novel algorithms for EDP using structural restrictions on the input graph, we then turn our attention towards the augmented graph, i.e., the graph obtained from the input graph after adding one edge between every terminal pair. In constrast to the input graph, where EDP is known to remain NP-hard even for treewidth two, a result by Zhou et al. (2000) shows that EDP can be solved in non-uniform polynomial time if the augmented graph has constant treewidth; we note that the possible improvement of this result to an fpt-algorithm has remained open since then. We show that this is highly unlikely by establishing the W[1]-hardness of the problem parameterized by the treewidth (and even feedback vertex set) of the augmented graph. Finally, we develop an fpt-algorithm for EDP by exploiting a novel structural parameter of the augmented graph.

Given a set of sources and a set of sinks in the two dimensional grid of size n, the disjoint paths (DP) problem is to connect every source to a distinct sink by a set of edge-disjoint paths. Let v be the total number of sources and sinks. In [3], Chan and Chin showed that without loss of generality we can assume v ≤ n ≤ 4v2. They also showed how to compress the grid optimally to a dynamic network (structure of the network may change depending on the paths found currently) of size O(√nv), and solve the problem in O(√nv3/2) time using augmenting path method in maximum flow. In this paper, we improve the time complexity of solving the DP problem to O(n3/4v3/4). The factor of improvement is as large as √v when n is Θ(v), while it is at least 4√v for n is Θ(v2).

A rotator graph was proposed as a topology for interconnection networks of parallel computers, and it is promising because of its small diameter and small degree. However, a rotator graph is a directed graph that sometimes behaves harmful when it is applied to actual problems. A bi-rotator graph is obtained by making each edge of a rotator graph bi-directional. A bi-rotator has a Hamilton cycle and it is also pan-cyclic. In this paper, we give an algorithm for the node-to-set disjoint paths problem in bi-rotator graphs with its evaluation results. The solution achieves some fault tolerance such as file distribution based information dispersal technique. The algorithm is of polynomial order of n for an n-bi-rotator graph. It is based on recursion and divided into three cases according to the distribution of destination nodes in classes into which all the nodes in a bi-rotator graph are categorized. The sum of lengths of paths obtained and the time complexity of the algorithm are estimated. Average performance of the algorithm is also evaluated by computer experiments.

An approximation algorithm for the Generalized [formula omitted]-Multicut problem

The disjoint paths problem in quadratic time

We consider the fine-grained complexity of sparse graph problems that currently have O(mn) time algorithms, where m is the number of edges and n is the number of vertices in the input graph. This class includes several important path problems on both directed and undirected graphs, including APSP, MWC (Minimum Weight Cycle), Radius, Eccentricities, BC (Betweenness Centrality), etc. We introduce the notion of a sparse reduction which preserves the sparsity of graphs, and we present near linear-time sparse reductions between various pairs of graph problems in the O(mn) class. There are many sub-cubic reductions between graph problems in the O(mn) class, but surprisingly few of these preserve sparsity. In the directed case, our results give a partial order on a large collection of problems in the O(mn) class (along with some equivalences), and many of our reductions are very nontrivial. In the undirected case we give two nontrivial sparse reductions: from MWC to APSP, and from unweighted ANSC (all nodes shortest cycles) to unweighted APSP. We develop a new ‘bit-sampling’ method for these sparse reductions on undirected graphs, which also gives rise to improved or simpler algorithms for cycle finding problems in undirected graphs. We formulate the the notion of MWC hardness, which is based on the assumption that a minimum weight cycle in a directed graph cannot be computed in time polynomially smaller than mn. Our sparse reductions for directed path problems in the O(mn) class establish that several problems in this class, including 2-SiSP (second simple shortest path), s-t Replacement Paths, Radius, Eccentricities and BC are MWC hard. Our sparse reductions give MWC hardness a status for the O(mn) class similar to 3SUM hardness for the quadratic class, since they show sub-mn hardness for a large collection of fundamental and well-studied graph problems that have maintained an O(mn) time bound for over half a century. We also identify Eccentricities and BC as key problems in the O(mn) class which are simultaneously MWC-hard, SETH-hard and k-DSH-hard, where SETH is the Strong Exponential Time Hypothesis, and k-DSH is the hypothesis that a dominating set of size k cannot be computed in time polynomially smaller than nk. Our framework using sparse reductions is very relevant to real-world graphs, which tend to be sparse and for which the O(mn) time algorithms are the ones typically used in practice, and not the O(n3) time algorithms.

Given four distinct vertices s1,s2,t1, and t2 of a graph G, the 2-disjoint paths problem is to determine two disjoint paths, p1 from s1 to t1 and p2 from s2 to t2, if such paths exist. Disjoint can mean vertex- or edge-disjoint. Both, the edge- and the vertex-disjoint version of the problem, are NP-hard in the case of directed graphs. For undirected graphs, we show that the O(mn)-time algorithm of Shiloach can be modified to solve the 2-vertex-disjoint paths problem in only O(n + mα(m,n)) time, where m is the number of edges in G, n is the number of vertices in G, and where α denotes the inverse of the Ackermann function. Our result also improves the running time for the 2-edge-disjoint paths problem on undirected graphs as well as the running times for the 2-vertex- and the 2-edge-disjoint paths problem on dags.

The problem of two node-disjoint paths is to identify two paths [Formula: see text] and [Formula: see text] from source [Formula: see text] to target [Formula: see text] without any common intermediate node in a communication network [Formula: see text], where each node (vertex) in [Formula: see text] denotes a process and each edge [Formula: see text] denotes a communication channel between nodes [Formula: see text] and [Formula: see text]. In this paper, we present the first adaptive stabilizing algorithm for finding a pair of node-disjoint paths in a semi-anonymous arbitrary network in [Formula: see text] rounds and the state-space complexity is [Formula: see text] bits per process, where [Formula: see text] is the diameter of the communication network. The algorithm assumes weakly fair distributed daemon and the knowledge of an upper bound on the number of processes by each process. If two disjoint paths exist between [Formula: see text] and [Formula: see text], two disjoint paths are guaranteed to be constructed. In addition, the algorithm detects if two node-disjoint paths exist or not. Since the proposed algorithm is stabilizing, it does not require initialization and is capable of withstanding transient faults. We view a fault that perturbs the state of the system but not its program as a transient fault. The proposed algorithm has a wide range of applications in ensuring reliability and security of sensor, mobile and fixed communication networks.