Dynamically Switching Vertices in Planar Graphs

We consider graphs whose vertices may be in one of two different states: either on or off . We wish to maintain dynamically such graphs under an intermixed sequence of updates and queries. An update may reverse the status of a vertex, by switching it either on or off , and may insert a new edge or delete an existing edge. A query tests whether any two given vertices are connected in the subgraph induced by the vertices that are on . We give efficient algorithms that maintain information about connectivity on planar graphs in O( log ³ n) amortized time per query, insert, delete, switch-on, and switch-off operation over sequences of at least Ω(n) operations, where n is the number of vertices of the graph. Received September 1997; revised January 1999.     

Maintaining bridge-connected and biconnected components on-line

We consider the twin problems of maintaining the bridge-connected components and the biconnected components of a dynamic undirected graph. The allowed changes to the graph are vertex and edge insertions. We give an algorithm for each problem. With simple data structures, each algorithm runs inO(n logn +m) time, wheren is the number of vertices andm is the number of operations. We develop a modified version of the dynamic trees of Sleator and Tarjan that is suitable for efficient recursive algorithms, and use it to reduce the running time of the algorithms for both problems toO(m(m,n)), where is a functional inverse of Ackermann's function. This time bound is optimal. All of the algorithms useO(n) space.Research at Princeton University supported in part by National Science Foundation Grant DCR-86-05962 and Office of Naval Research Contract N00014-91-J-1463.This work was partially done while the author was at the Department of Computer Science, Princeton University, Princeton, NJ 08544, USA.     

Dynamic bottleneck optimization for k-edge and 2-vertex connectivity

We consider the problem of updating efficiently the minimum value b over a weighted graph, so that edges with a cost less than b induce a spanning subgraph satisfying a k-edge or 2-vertex connectivity constraint, when the cost of an edge of the graph is updated. Our results include update algorithms of almost linear time (up to poly-logarithmic factors) in the number of vertices for all considered connectivity constraints (for fixed k), and a worst case construction showing that these algorithms are almost optimal in their class.     

An Incremental Distributed Algorithm for Computing Biconnected Components in Dynamic Graphs

This paper describes a distributed algorithm for computing the biconnected components of a dynamically changing graph. Our algorithm has a worst-case communication complexity of O(b+c) messages for an edge insertion and O(b'+c) messages for an edge removal, and a worst-case time complexity of O(c) for both operations, where c is the maximum number of biconnected components in any of the connected components during the operation, b is the number of nodes in the biconnected component containing the new edge, and b' is the number of nodes in the biconnected component just before the deletion. The algorithm is presented in two stages. First, a serial algorithm is presented in which topology updates occur one at a time. Then, building on the serial algorithm, an algorithm is presented in which concurrent update requests are serialized within each connected component. The problem is motivated by the need to implement causal ordering of messages efficiently in a dynamically changing communication structure. Received January 1995; revised February 1997.     

Canonical density control

The Sparse Table is a data structure for controlling density in an array which was first proposed in 1981 and has recently reappeared as a component of cache-oblivious data structures. All existing variants of the Sparse Table divide the array into blocks that have a calibrator tree above them. We show that the same amortized complexity can be achieved without this auxiliary structure, obtaining a canonical data structure that can be updated by conceptually simpler algorithms.     

On the false-positive rate of Bloom filters

Bloom filters are a randomized data structure for membership queries dating back to 1970. Bloom filters sometimes give erroneous answers to queries, called false positives. Bloom analyzed the probability of such erroneous answers, called the false-positive rate, and Bloom's analysis has appeared in many publications throughout the years. We show that Bloom's analysis is incorrect and give a correct analysis.     

Finding the k Shortest Paths in Parallel

A concurrent-read exclusive-write PRAM algorithm is developed to find the k shortest paths between pairs of vertices in an edge-weighted directed graph. Repetitions of vertices along the paths are allowed. The algorithm computes an implicit representation of the k shortest paths to a given destination vertex from every vertex of a graph with n vertices and m edges, using O(m+nk log ² k) work and O( log^3k log ^*k+ log n( log log k+ log ^*n)) time, assuming that a shortest path tree rooted at the destination is pre-computed. The paths themselves can be extracted from the implicit representation in O( log k + log n) time, and O(n log n +L) work, where L is the total length of the output. Received July 2, 1997; revised June 18, 1998.     

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.     

Double hashing with passbits

Double hashing with bucket capacity one is augmented with multiple passbits to obtain significant reduction to unsuccessful search lengths. This improves the analysis of Martini et al. [P.M. Martini, W.A. Burkhard, Double hashing with multiple passbits, Internat. J. Found. Theoret. Comput. Sci. 14 (6) (2003) 1165-1188] by providing a closed form expression for the expected unsuccessful search lengths.     

Using spine decompositions to efficiently solve the length-constrained heaviest path problem for trees

The length-constrained heaviest path (LCHP) in a weighted tree T, where each edge is assigned a weight and a length, is the path P in T with maximum total path weight and total path length bounded by a given value B. This paper presents an O(nlogn) time LCHP algorithm which utilizes a data structure constructed from the spine decomposition of the input tree. This is an improvement over the existing algorithm by Wu et al. (1999), which runs in O(nlog²n) time. Our method also improves on a previous O(nlogn) time algorithm by Kim (2005) for the special case of finding a longest nonnegative path in a constant degree tree in that we can handle trees of arbitrary degree within the same time bounds.     

A new analysis of the false positive rate of a Bloom filter

A Bloom filter is a space-efficient data structure used for probabilistic set membership testing. When testing an object for set membership, a Bloom filter may give a false positive. The analysis of the false positive rate is a key to understanding the Bloom filter and applications that use it. We show experimentally that the classic analysis for false positive rate is wrong. We formally derive a correct formula using a balls-and-bins model and show how to numerically compute the new, correct formula in a stable manner. We also prove that the new formula always results in a predicted greater false positive rate than the classic formula. This correct formula is numerically compared to the classic formula for relative error - for a small Bloom filter the prediction of false positive rate will be in error when the classic formula is used.     

Maintaining Spanning Trees of Small Diameter

Given a graph G with m edges and n nodes, a spanning tree T of G , and an edge e that is being deleted from or inserted into G , we give efficient O(n) algorithms to compute a possible swap for e that minimizes the diameter of the new spanning tree. This problem arises in high-speed networks, particularly in optical networks. Received January 1995; revised February 1997.     

Speedup for a periodic subgraph miner

Given a series G={G₀,G₁,…,GT} of graphs encompassing V vertices and E edges, a periodic graph is a spatially as well as temporally maximal subgraph of a subsequence of G in the form , where n is not smaller than some predetermined threshold value σ. An algorithm for finding all such subgraphs is proposed taking time O((E+V)T²ln(T/σ)), which is faster by a factor of T than the method previously available.     

Fully dynamic biconnectivity in graphs

We present an algorithm for maintaining the biconnected components of a graph during a sequence of edge insertions and deletions. It requires linear storage and preprocessing time. The amortized running time for insertions and for deletions isO(m ^2/3 ), wherem is the number of edges in the graph. Any query of the form ‘Are the verticesu andv biconnected?’ can be answered in timeO(1). This is the first sublinear algorithm for this problem. We can also output all articulation points separating any two vertices efficiently. If the input is a plane graph, the amortized running time for insertions and deletions drops toO(√n logn) and the query time isO(log² n), wheren is the number of vertices in the graph. The best previously known solution takes timeO(n ^2/3 ) per update or query.     

Trading uninitialized space for time

The design of efficient graph algorithms usually precludes the test of edge existence, because an efficient support of that operation already requires time for the initialization of an adjacency-matrix representation. We describe an alternative representation of static directed graphs taking Θ(n+m) initialization time and using Θ(n²) space, which supports the efficient implementation of all usual operations on static graphs. The sparse graph representation allows the design of efficient graph algorithms using both iteration over all vertices adjacent with a given vertex and edge-existence operations, although at the expense of additional (uninitialized) space which may, nevertheless, be used for other purposes. To the best of our knowledge, the representation leads to the first graph algorithms with the disconcerting property that the time complexity is better than the space complexity.     

k-Restricted rotation distance between binary trees

The restricted rotation distancedR(S,T) between two binary trees S, T of n vertices is the minimum number of rotations to transform S into T, where rotations take place at the root of S, or at the right child of the root. A sharp upper bound dR(S,T)?4n−8 is known, based on group theory [S. Cleary, J. Taback, Bounding restricted rotation distance, Information Processing Letters 88 (5) (2003) 251-256]. We refine this bound to a sharp dR(S,T)?4n−8−ρS−ρT, where ρS and ρT are the numbers of vertices in the rightmost vertex chains of the two trees, using an elementary transformation algorithm. We then generalize the concept to k-restricted rotation, by allowing rotations to take place at all the vertices of the highest k levels of the tree, and study the new distance for k=2. The case k?3 is essentially open.     

List update with probabilistic locality of reference

In this paper we study the performance of list update algorithms under arbitrary distributions that exhibit strict locality of reference and prove that Move-To-Front (MTF) is the best list update algorithm under any such distribution. We also show that the performance of MTF depends on the amount of locality of reference, while the performance of any static list update algorithm is independent of the amount of locality.     

Lower bounds on the OBDD size of two fundamental functions' graphs

Ordered Binary Decision Diagrams (OBDDs) are a data structure for Boolean functions which supports many useful operations. Among others it finds applications in CAD, model checking, and symbolic graph algorithms. Nevertheless, many simple functions are known to have exponential OBDD size with respect to their number of variables. In order to investigate the limits of symbolic graph algorithms which work on OBDD-represented graph instances, it is useful to have simply-structured graphs whose OBDD representation has exponential size. Therefore, we consider two fundamental functions with exponential lower bounds on their OBDD size and transfer these results to their corresponding graphs. Concretely, we consider the Indirect Storage Access function and the Hidden Weighted Bit function.     

On the existence and construction of non-extreme (a,b)-trees

In amortized analysis of data structures, it is standard to assume that initially the structure is empty. Usually, results cannot be established otherwise. In this paper, we investigate the possibilities of establishing such results for initially non-empty multi-way trees.