Maintaining the Classes of 4-Edge-Connectivity in a Graph On-Line

Two vertices of an undirected graph are called k -edge-connected if there exist k edge-disjoint paths between them (equivalently, they cannot be disconnected by the removal of less than k edges from the graph). Equivalence classes of this relation are called classes of k -edge-connectivity or k -edge-connected components. This paper describes graph structures relevant to classes of 4 -edge-connectivity and traces their transformations as new edges are inserted into the graph. Data structures and an algorithm to maintain these classes incrementally are given. Starting with the empty graph, any sequence of q Same-4-Class? queries and n Insert-Vertex and m Insert-Edge updates can be performed in O(q + m + n log n) total time. Each individual query requires O(1) time in the worst-case. In addition, an algorithm for maintaining the classes of k -edge-connectivity (k arbitrary) in a (k-1) -edge-connected graph is presented. Its complexity is O(q + m + n) , with O(M +k ² n log (n/k)) preprocessing, where M is the number of edges initially in the graph and n is the number of its vertices. Received July 5, 1995; revised October 21, 1996.     

A new algorithm for shortest paths among obstacles in the plane

We introduce a new algorithm for computing Euclidean shortest paths in the plane in the presence of polygonal obstacles. In particular, for a given start points, we build a planar subdivision (ashortest path map) that supports efficient queries for shortest paths froms to any destination pointt. The worst-case time complexity of our algorithm isO(kn log² n), wheren is the number of vertices describing the polygonal obstacles, andk is a parameter we call the illumination depth of the obstacle space. Our algorithm usesO(n) space, avoiding the possibly quadratic space complexity of methods that rely on visibility graphs. The quantityk is frequently significantly smaller thann, especially in some of the cases in which the visibility graph has quadratic size. In particular,k is bounded above by the number of different obstacles that touch any shortest path froms.Partially supported by NSF Grants IRI-8710858 and ECSE-8857642 and by a grant from Hughes Research Laboratories, Malibu, CA.     

Compact Routing on Chordal Rings of Degree 4

A chordal ring G(n;c) of degree 4 is a ring of n nodes with chords connecting each vertex i to the vertex (i + c) mod n . In this paper we investigate compact routing schemes on such networks. We show an optimal boolean routing scheme for any such network that requires O( log n) bits of storage at each node, and O(1) time to compute a shortest path to any destination. This improves on the results of [16] which gives a linear time algorithm for such networks and [6] where efficient routing schemes for certain fixed values of c were developed. Further, we show several bounds on interval routing schemes for such networks. We show that while every chordal ring has an optimal interval routing scheme with at most intervals on any edge, there exist chordal rings for which any optimal interval routing scheme that labels the vertices around the ring in the graph requires intervals on some edges. Additionally, there are chordal rings which admit no optimal one-interval routing schemes, regardless of the vertex labeling. We also consider interval routing schemes under relaxed requirements for the lengths of paths. Received September 5, 1997; revised December 1, 1997.     

Optimal parallel algorithms for multiple updates of minimum spanning trees

Parallel updates of minimum spanning trees (MSTs) have been studied in the past. These updates allowed a single change in the underlying graph, such as a change in the cost of an edge or an insertion of a new vertex. Multiple update problems for MSTs are concerned with handling more than one such change. In the sequential case multiple update problems may be solved using repeated applications of an efficient algorithm for a single update. However, for efficiency reasons, parallel algorithms for multiple update problems must consider all changes to the underlying graph simultaneously. In this paper we describe parallel algorithms for updating an MST whenk new vertices are inserted or deleted in the underlying graph, when the costs ofk edges are changed, or whenk edge insertions and deletions are performed. For multiple vertex insertion update, our algorithm achieves time and processor bounds ofO(log n·logk) and nk/(logn·logk), respectively, on a CREW parallel random access machine. These bounds are optimal for dense graphs. A novel feature of this algorithm is a transformation of the previous MST andk new vertices to a bipartite graph which enables us to obtain the above-mentioned bounds.     

An efficient parallel algorithm for shortest paths in planar layered digraphs

Computing shortest paths in a directed graph has received considerable attention in the sequential RAM model of computation. However, developing a polylog-time parallel algorithm that is close to the sequential optimal in terms of the total work done remains an elusive goal. We present a first step in this direction by giving efficient parallel algorithms for shortest paths in planar layered digraphs.We show that these graphs admit special kinds of separators calledone- way separators which allow the paths in the graph to cross it only once. We use these separators to give divide- and -conquer solutions to the problem of finding the shortest paths between any two vertices. We first give a simple algorithm that works in the CREW model and computes the shortest path between any two vertices in ann-node planar layered digraph in timeO(log² n) usingn/logn processors. We then use results of Aggarwal and Park [1] and Atallah [4] to improve the time bound toO(log² n) in the CREW model andO(logn log logn) in the CREW model. The processor bounds still remain asn/logn for the CREW model andn/log logn for the CRCW model.Support for the first and third authors was provided in part by a National Science Foundation Presidential Young Investigator Award CCR-9047466 with matching funds from IBM, by NSF Research Grant CCR-9007851, by Army Research Office Grant DAAL03-91-G-0035, and by the Office of Naval Research and the Advanced Research Projects Agency under Contract N00014-91-J-4052, ARPA, Order 8225. Support for the second author was provided in part by NSF Research Grant CCR-9007851, by Army Research Office Grant DAAL03-91-G-0035, and by the Office of Naval Research and the Advanced Research Projects Agency under Contract N00014-91-J-4052 and ARPA Order 8225.     

Proximity problems for points on a rectilinear plane with rectangular obstacles

We consider the following four problems for a setS ofk points on a plane, equipped with the rectilinear metric and containing a setR ofn disjoint rectangular obstacles (so that distance is measured by a shortest rectilinear path avoiding obstacles inR): (a) find aclosest pair of points inS, (b) find anearest neighbor for each point inS, (c) compute the rectilinearVoronoi diagram ofS, and (d) compute a rectilinearminimal spanning tree ofS. We describeO ((n+k) log(n+k))-time sequential algorithms for (a) and (b) based onplane-sweep, and the consideration of geometrically special types of shortest paths, so-calledz-first paths. For (c) we present anO ((n+k) log(n+k) logn)-time sequential algorithm that implements a sophisticateddivide-and-conquer scheme with an addedextension phase. In the extension phase of this scheme we introduce novel geometric structures, in particular so-calledz-diagrams, and techniques associated with the Voronoi diagram. Problem (d) can be reduced to (c) and solved inO ((n+k) log(n+k) logn) time as well. All our algorithms arenear-optimal, as well as easy to implement. An extended abstract appeared inProc. 13th Conf. on the Foundations of Software Technology and Theoretical Computer Science, Bombay, 1993, Springer-Verlag, pp. 218–227. Sumanta Guha was supported in part by a UW-Milwaukee Graduate School Research Committee Award. Ichiro Suzuki was supported in part by the National Science Foundation under Grants CCR-9004346 and IRI-9307506, the Office of Naval Research under Grant N00014-94-1-0284, and an endowed chair supported by Hitachi Ltd. at the Faculty of Engineering Science, Osaka University.     

Finding a Region with the Minimum Total L1 Distance from Prescribed Terminals

Given k terminals and n axis-parallel rectangular obstacles on the plane, our algorithm finds a plane region R ^* such that, for any point p in R ^* , the total length of the k shortest rectilinear paths connecting p and the k terminals without passing through any obstacle is minimum. The algorithm is output-sensitive, and takes O((K+n) log n) time and O(K+n) space if k is a fixed constant, where K is the total number of polygonal vertices of the found region R ^* .     

A Fully Dynamic Approximation Scheme for Shortest Paths in Planar Graphs

In this paper we give a fully dynamic approximation scheme for maintaining all-pairs shortest paths in planar networks. Given an error parameter such that , our algorithm maintains approximate all-pairs shortest paths in an undirected planar graph G with nonnegative edge lengths. The approximate paths are guaranteed to be accurate to within a 1+ factor. The time bounds for both query and update for our algorithm is O( ^-1 n ^2/3 log ² n log D) , where n is the number of nodes in G and D is the sum of its edge lengths. The time bound for the queries is worst case, while that for the additions is amortized. Our approximation algorithm is based upon a novel technique for approximately representing all-pairs shortest paths among a selected subset of the nodes by a sparse substitute graph. Received January 1995; revised February 1997.     

An Efficient Algorithm for Finding All Hinge Vertices on Trapezoid Graphs

The distance between at least two vertices becomes longer after the removal of a hinge vertex. Thus a faulty hinge vertex will increase the overall communication cost in a network. Therefore, finding the set of all hinge vertices in a graph can be used to identify critical nodes in a real network. An O(n log n) time algorithm has been proposed here to find all hinge vertices of a trapezoid graph with n vertices.     

Semidynamic Algorithms for Maintaining Single-Source Shortest Path Trees

We consider the problem of updating a single-source shortest path in either a directed or an undirected graph, with positive real edge weights. Our algorithms for the incremental problem (handling edge insertions and cost decrements) work for any graph; they have optimal space requirements and query time, but their performances depend on the class of the considered graph. The cost of updates is computed in terms of amortized complexity and depends on the size of the output modifications. In the case of graphs with bounded genus (including planar graphs), graphs with bounded arboricity (including bounded degree graphs), and graphs with bounded treewidth, the incremental algorithms require O(log n) amortized time per vertex update, where a vertex is considered updated if it reduces its distance from the source. For general graphs with n vertices and m edges our incremental solution requires O( log n) amortized time per vertex update. We also consider the decremental problem for planar graphs, providing algorithms and data structures with analogous performances. The algorithms, based on Dijkstra's technique [6], require simple data structures that are really suitable for a practical and straightforward implementation. Received January 1995; revised February 1997.     

Searching among intervals and compact routing tables

Shortest paths in weighted directed graphs are considered within the context of compact routing tables. Strategies are given for organizing compact routing tables so that extracting a requested shortest path will takeo(k logn) time, wherek is the number of edges in the path andn is the number of vertices in the graph. The first strategy takesO (k+logn) time to extract a requested shortest path. A second strategy takes (k) time on average, assuming alln(n–1) shortest paths are equally likely to be requested. Both strategies introduce techniques for storing collections of disjoint intervals over the integers from 1 ton, so that identifying the interval within which a given integer falls can be performed quickly.This research was supported in part by the National Science Foundation under Grants CCR-9001241 and CCR-9322501 and by the Office of Naval Research under Contract N00014-86-K-0689.     

Improved Algorithms for Constructing Fault-Tolerant Spanners

Abstract. Let S be a set of n points in a metric space, and let k be a positive integer. Algorithms are given that construct k -fault-tolerant spanners for S . If in such a spanner at most k vertices and/ or edges are removed, then each pair of points in the remaining graph is still connected by a ``short' path. First, an algorithm is given that transforms an arbitrary spanner into a k -fault-tolerant spanner. For the Euclidean metric in R ^d , this leads to an O(n log n + c ^k n) -time algorithm that constructs a k -fault-tolerant spanner of degree O(c ^k ) , whose total edge length is O(c ^k ) times the weight of a minimum spanning tree of S , for some constant c . For constant values of k , this result is optimal. In the second part of the paper, algorithms are presented for the Euclidean metric in R ^d . These algorithms construct (i) in O(n log n + k ² n) time, a k -fault-tolerant spanner with O(k ² n) edges, and (ii) in O(k n log n) time, such a spanner with O(k n log n) edges.     

Finding a Region with the Minimum Total L 1 Distance from Prescribed Terminals

Given k terminals and n axis-parallel rectangular obstacles on the plane, our algorithm finds a plane region R* such that, for any point p in R*, the total length of the k shortest rectilinear paths connecting p and the k terminals without passing through any obstacle is minimum. The algorithm is output-sensitive, and takes O((K+n) log n) time and O(K+n) space if k is a fixed constant, where K is the total number of polygonal vertices of the found region R*.     

Efficient parallel algorithms for computing all pair shortest paths in directed graphs

We present parallel algorithms for computing all pair shortest paths in directed graphs. Our algorithm has time complexityO(f(n)/p+I(n)logn) on the PRAM usingp processors, whereI(n) is logn on the EREW PRAM, log logn on the CCRW PRAM,f(n) iso(n ³). On the randomized CRCW PRAM we are able to achieve time complexityO(n ³/p+logn) usingp processors. A preliminary version of this paper was presented at the 4th Annual ACM Symposium on Parallel Algorithms and Architectures, June 1992. Support by NSF Grant CCR 90-20690 and PSC CUNY Awards #661340 and #662478.     

Output-Sensitive Reporting of Disjoint Paths

A k -path query on a graph consists of computing k vertex-disjoint paths between two given vertices of the graph, whenever they exist. In this paper we study the problem of performing k -path queries, with , in a graph G with n vertices. We denote with the total length of the reported paths. For , we present an optimal data structure for G that uses O(n) space and executes k -path queries in output-sensitive time. For triconnected planar graphs, our results make use of a new combinatorial structure that plays the same role as bipolar (st ) orientations for biconnected planar graphs. This combinatorial structure also yields an alternative construction of convex grid drawings of triconnected planar graphs. Received August 24, 1996; revised April 8, 1997.     

Fast 3-coloring Triangle-Free Planar Graphs

Although deciding whether the vertices of a planar graph can be colored with three colors is NP-hard, the widely known Grötzsch’s theorem states that every triangle-free planar graph is 3-colorable. We show the first o(n ²) algorithm for 3-coloring vertices of triangle-free planar graphs. The time complexity of the algorithm is $\mathcal{O}(n\log n)Although deciding whether the vertices of a planar graph can be colored with three colors is NP-hard, the widely known Gr?tzsch’s theorem states that every triangle-free planar graph is 3-colorable. We show the first o(n ²) algorithm for 3-coloring vertices of triangle-free planar graphs. The time complexity of the algorithm is O(nlogn)\mathcal{O}(n\log n) .     

A New Approach for the Geodesic Voronoi Diagram of Points in a Simple Polygon and Other Restricted Polygonal Domains

We introduce a new method for computing the geodesic Voronoi diagram of point sites in a simple polygon and other restricted polygonal domains. Our method combines a sweep of the polygonal domain with the merging step of a usual divide-and-conquer algorithm. The time complexity is O((n+k) log(n+k)) where n is the number of vertices and k is the number of points, improving upon previously known bounds. Space is O(n+k) . Other polygonal domains where our method is applicable include (among others) a polygonal domain of parallel disjoint line segments and a polygonal domain of rectangles in the L ₁ metric. Received February 15, 1996; revised November 2, 1996.     

On-line maintenance of triconnected components with SPQR-trees

We consider the problem of maintaining on-line the triconnected components of a graphG. Letn be the current number of vertices ofG. We present anO(n)-space data structure that supports insertions of vertices and edges, and queries of the type “Are there three vertex-disjoint paths between verticesv ₁ andv ₂?” A sequence ofk operations takes timeO(k·α(k, n)) ifG is biconnected(α(k, n) denotes the well-known Ackermann's function inverse), and timeO(n logn+k) ifG is not biconnected. Note that the bounds do not depend on the number of edges ofG. We use theSPQR-tree, a versatile data structure that represents the decomposition of a biconnected graph with respect to its triconnected components, and theBC-tree, which represents the decomposition of a connected graph with respect to its biconnected components.     

Improved algorithm for all pairs shortest paths

We present an improved algorithm for all pairs shortest paths. For a graph of n vertices our algorithm runs in O(n³(loglogn/logn)^5/7) time. This improves the best previous result which runs in O(n³(loglogn/logn)^1/2) time.     

Approximating Minimum Feedback Sets and Multicuts in Directed Graphs

This paper deals with approximating feedback sets in directed graphs. We consider two related problems: the weighted feedback vertex set (FVS) problem, and the weighted feedback edge set (FES) problem. In the {FVS} (resp. FES) problem, one is given a directed graph with weights (each of which is at least one) on the vertices (resp. edges), and is asked to find a subset of vertices (resp. edges) with minimum total weight that intersects every directed cycle in the graph. These problems are among the classical NP-hard problems and have many applications. We also consider a generalization of these problems: subset-fvs and subset-fes, in which the feedback set has to intersect only a subset of the directed cycles in the graph. This subset consists of all the cycles that go through a distinguished input subset of vertices and edges, denoted by X . This generalization is also NP-hard even when |X|=2 . We present approximation algorithms for the subset-fvs and subset-fes problems. The first algorithm we present achieves an approximation factor of O(log ² |X|) . The second algorithm achieves an approximation factor of O(min{log τ ^* log log τ ^* , log n log log n)} , where τ ^* is the value of the optimum fractional solution of the problem at hand, and n is the number of vertices in the graph. We also define a multicut problem in a special type of directed networks which we call circular networks, and show that the subset-fes and subset-fvs problems are equivalent to this multicut problem. Another contribution of our paper is a combinatorial algorithm that computes a (1+ɛ) approximation to the fractional optimal feedback vertex set. Computing the approximate solution is much simpler and more efficient than general linear programming methods. All of our algorithms use this approximate solution. Received May 31, 1995; revised June 11, 1996, and October 9, 1996.