A faster parallel algorithm for a matrix searching problem

We give an improved parallel algorithm for the problem of computing the tube minima of a totally monotonen ×n ×n matrix, an important matrix searching problem that was formalized by Aggarwal and Park and has many applications. Our algorithm runs inO(log logn) time withO(n²/log logn) processors in theCRCW-PRAM model, whereas the previous best ran inO((log logn)²) time withO(n²/(log logn)² processors, also in theCRCW-PRAM model. Thus we improve the speed without any deterioration in thetime ×processors product. Our improved bound immediately translates into improvedCRCW-PRAM bounds for the numerous applications of this problem, including string editing, construction of Huffmann codes and other coding trees, and many other combinatorial and geometric problems.This research was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, the Air Force Office of Scientific Research under Grant AFOSR-90-0107, the National Science Foundation under Grant DCR-8451393, and the National Library of Medicine under Grant R01-LM05118. Part of the research was done while the author was at Princeton University, visiting the DIMACS center.     

An efficient algorithm for maxdominance, with applications

Given a planar setS ofn points,maxdominance problems consist of computing, for everyp S, some function of the maxima of the subset ofS that is dominated byp. A number of geometric and graph-theoretic problems can be formulated as maxdominance problems, including the problem of computing a minimum independent dominating set in a permutation graph, the related problem of finding the shortest maximal increasing subsequence, the problem of enumerating restricted empty rectangles, and the related problem of computing the largest empty rectangle. We give an algorithm for optimally solving a class of maxdominance problems. A straightforward application of our algorithm yields improved time bounds for the above-mentioned problems. The techniques used in the algorithm are of independent interest, and include a linear-time tree computation that is likely to arise in other contexts.The research of this author was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, and the National Science Foundation under Grant DCR-8451393, with matching funds from AT&T.This author's research was supported by the National Science Foundation under Grant DCR-8506361.     

Topological numbering of features on a mesh

Assume we are given ann ×n binary image containing horizontally convex features; i.e., for each feature, each of its row's pixels form an interval on that row. In this paper we consider the problem of assigning topological numbers to such features, i.e., assign a number to every featuref so that all features to the left off in the image have a smaller number assigned to them. This problem arises in solutions to the stereo matching problem. We present a parallel algorithm to solve the topological numbering problem inO(n) time on ann ×n mesh of processors. The key idea of our solution is to create a tree from which the topological numbers can be obtained even though the tree does not uniquely represent the to the left of relationship of the features.The work of M. J. Atallah was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, and the National Science Foundation under Grant DCR-8451393, with matching funds from AT&T. Part of this work was done while he was a Visiting Scientist at the Center for Advanced Architectures project of the Research Institute for Advanced Computer Science, NASA Ames Research Center, Moffett Field, CA 94035, USA. S. E. Hambrusch's work was supported by the Office of Naval Research under Contracts N00014-84-K-0502 and N00014-86K-0689, and by the National Science Foundation under Grant MIP-87-15652. Part of this work was done while she was visiting the International Computer Science Institute, Berkeley, CA 94704, USA. The work of L. E. TeWinkel was supported by the Office of Naval Research under Contract N00014-86K-0689.     

Parallel algorithms for some functions of two convex polygons

Let P andQ be two convex,n-vertex polygons. We consider the problem of computing, in parallel, some functions ofP andQ whenP andQ are disjoint. The model of parallel computation we consider is the CREW-PRAM, i.e., it is the synchronous shared-memory model where concurrent reads are allowed but no two processors can simultaneously attempt to write in the same memory location (even if they are trying to write the same thing). We show that a CREW-PRAM havingn ^1/k processors can compute the following functions in O(k¹⁺) time: (i) the common tangents betweenP andQ, and (ii) the distance betweenP andQ (and hence a straight line separating them). The positive constant can be made arbitrarily close to zero. Even with a linear number of processors, it was not previously known how to achieve constant time performance for computing these functions. The algorithm for problem (ii) is easily modified to detect the case of zero distance as well.This research was supported by the Office of Naval Research under Grants N00014-84-K-0502 and N00014-86-K-0689, and the National Science Foundation under Grant DCR-8451393, with matching funds from AT&T.     

AE1: An extension matrix approximate method for the general covering problem

A new approach, the extension matrix approach, is introduced and used to show that some optimization problems in general covering problem areNP-hard. Approximate solutions for these problems are given. Combining these approximate solutions, this paper presents an approximately optimal covering algorithm,AE1. Implementation shows thatAE1 is efficient and gives optimal or near optimal results.This research was supported in part by the National Science Foundation under Grant DCR 84-06801, Office of Naval Research under Grant N00014-82-K-0186, Defense Advanced Research Project Agency under Grant N00014-K-85-0878, and Education Ministry of the People's Republic of China.On leave from Harbin Institute of Technology, Harbin, China.     

Linear-time algorithms for visibility and shortest path problems inside triangulated simple polygons

Given a triangulation of a simple polygonP, we present linear-time algorithms for solving a collection of problems concerning shortest paths and visibility withinP. These problems include calculation of the collection of all shortest paths insideP from a given source vertexS to all the other vertices ofP, calculation of the subpolygon ofP consisting of points that are visible from a given segment withinP, preprocessingP for fast "ray shooting" queries, and several related problems.Work on this paper by this author has been supported by Office of Naval Research Grant N00014-82-K-0381, National Science Foundation Grant No. NSF-DCR-83-20085, and by grants from the Digital Equipment Corporation, the IBM Corporation, and from the U.S.-Israel Binational Science Foundation.Work on this paper by this author has been supported by National Science Foundation Grant DCR-86-05962.     

Optimal cooperative search in fractional cascaded data structures

Fractional cascading is a technique designed to allow efficient sequential search in a graph with catalogs of total sizen. The search consists of locating a key in the catalogs along a path. In this paper we show how to preprocess a variety of fractional cascaded data structures whose underlying graph is a tree so that searching can be done efficiently in parallel. The preprocessing takesO(logn) time withn/logn processors on an EREW PRAM. For a balanced binary tree, cooperative search along root-to-leaf paths can be done inO((logn)/logp) time usingp processors on a CREW PRAM. Both of these time/processor constraints are optimal. The searching in the fractional cascaded data structure can be either explicit, in which the search path is specified before the search starts, or implicit, in which the branching is determined at each node. We apply this technique to a variety of geometric problems, including point location, range search, and segment intersection search.An earlier version of this work appears inProceedings of the 2nd Annual ACM Symposium on Parallel Algorithms and Architectures, July 1990, pp. 307–316. The first author's support was provided in part by National Science Foundation Grant CCR-9007851, by the U.S. Army Research Office under Grants DAAL03-91-G-0035 and DAAH04-93-0134, and by the Office of Naval Research and the Advanced Research Projects Agency under Contract N00014-91-J-4052, ARPA Order 8225. This research was performed while the second author was at Brown University. Support was provided in part by an NSF Presidential Young Investigator Award CCR-9047466, with matching funds from IBM, by National Science Foundation Grant CCR-9007851, by the U.S. Army Research Office under 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.     

Designing networks with compact routing tables

Classes of network topologies are identified in which shortest-path information can be succinctly stored at the nodes, if they are assigned suitable names. The naming allows each edge at a node to be labeled with zero or more intervals of integers, representing all nodes reachable by a shortest path via that edge. Starting with the class of outerplanar networks, a natural hierarchy of networks is established, based on the number of intervals required. The outerplanar networks are shown to be precisely the networks requiring just one interval per edge. An optimal algorithm is given for determining the labels for edges in outerplanar networks.The research of this author was supported in part by the National Science Foundation under Grant DCR-8320124, and by the Office of Naval Research on contract N 00014-86-K-0689.The research of this author was supported in part by the National Science Foundation under Grant DCR-8320124.     

Distributed match-making

In many distributed computing environments, processes are concurrently executed by nodes in a store- and-forward communication network. Distributed control issues as diverse as name server, mutual exclusion, and replicated data management involve making matches between such processes. We propose a formal problem called distributed match-making as the generic paradigm. Algorithms for distributed match-making are developed and the complexity is investigated in terms of messages and in terms of storage needed. Lower bounds on the complexity of distributed match-making are established. Optimal algorithms, or nearly optimal algorithms, are given for particular network topologies.The work of the second author was supported in part by the Office of Naval Research under Contract N00014-85-K-0168, by the Office of Army Research under Contract DAAG29-84-K-0058, by the National Science Foundation under Grant DCR-83-02391, and by the Defence Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125. Current address of both authors: CWI, Kruislaan 413, 1098 SJ Amsterdam, The Netherlands.     

The accelerated centroid decomposition technique for optimal parallel tree evaluation in logarithmic time

A new general parallel algorithmic technique for computations on trees is presented. In particular, it provides the firstn/logn processor,O(logn)-time deterministic EREW PRAM algorithm for expression tree evaluation. The technique solves many other tree problems within the same complexity bounds.Richard Cole was supported in part by NSF Grants DCR-84-01633 and CCR-8702271, ONR Grant N00014-85-K-0046 and by an IBM faculty development award. Uzi Vishkin was supported in part by NSF Grants NSF-CCR-8615337 and NSF-DCR-8413359, ONR Grant N00014-85-K-0046, by the Applied Mathematical Science subprogram of the office of Energy Research, U.S. Department of Energy under Contract DE-AC02-76ER03077 and the Foundation for Research in Electronics, Computers and Communication, administered by the Israeli Academy of Sciences and Humanities.     

Checking similarity of planar figures

Two planar figures aresimilar if a scaled version of one of them can be moved so that it coincides with the second figure. The problem of checking whether two planar figures are similar is relevant to both computational geometry and pattern recognition. An efficient algorithm is known for checking whether two polygonsP andQ are similar⁽¹⁾ The purpose of this note is to give an efficient algorithm for checking whether two planar figuresP andQ are similar when the figures are no longer constrained to be polygons. We give anO(n logn) time algorithm for solving this problem when each figure consists of a collection of (possibly intersecting) straight line segments, circles, and ellipses. Our algorithm can easily be modified for figures which include other geometric patterns as well. We also prove that our algorithm is optimal.This work was partially supported by the Office of Naval Research under Contract N00014-84-K-0502.     

A modular drinking philosophers algorithm

Summary A variant of the drinking philosophers algorithm of Chandy and Misra is described and proved correct in a modular way. The algorithm of Chandy and Misra is based on a particular dining philosophers algorithm and relies on certain properties of its implementation. The drinking philosophers algorithm presented in this paper is able to use an arbitrary dining philosophers algorithm as a subroutine; nothing about the implementation needs to be known, only that it solves the dining philosophers problem. An important advantage of this modularity is that by substituting a more time-efficient dining philosophers algorithm than the one used by Chandy and Misra, a drinking philosophers algorithm withO(1) worst-case waiting time is obtained, whereas the drinking philosophers algorithm of Chandy and Misra hasO(n) worst-case waiting time (forn philosophers). Careful definitions are given to distinguish the drinking and dining philosophers problems and to specify varying degrees of concurrency. Jennifer L. Welch received her B.A. in 1979 from the University of Texas at Austin, and her S.M. and Ph.D. from the Massachusetts Institute of Technology in 1984 and 1988 respectively. She has been a member of technical staff at GTE Laboratories Incorporated in Waltham, Massachusetts and an assistant professor at the University of North Carolina at Chapel Hill. She is currently an assistant professor at Texas A&M University. Her research interests include algorithms and lower bounds for distributed computing.Much of this work was performed while this author was at the Laboratory for Computer Science, Massachusetts Institute of Technology, supported by the Advanced Research Projects Agency of the Department of Defense under contract N00014-83-K-0125, the National Science Foundation under grants DCR-83-02391 and CCR-86-11442, the Office of Army Research under contract DAAG29-84-K-0058, and the Office of Naval Research under contract N00014-85-K-0168. This author was also supported in part by NSF grant CCR-9010730, an IBM Faculty Development Award, and NSF Presidential Young Investigator Award CCR-9158478This author was supported by the Office of Naval Research under contract N00014-91-J-1046, the Advanced Research Projects Agency of the Department of Defense under contract N00014-89-J-1988, and the National Science Foundation under grant CCR-89-15206. The photograph and autobiography of Professor N.A. Lynch were published in Volume 6, No. 2, 1992 on page 121     

A note on weighted distributed match-making

In many distributed computing environments, processes are concurrently executed by nodes in a store-and-forward network. Distributed control issues as diverse as name-server, mutual exclusion, and replicated data management, involve making matches between processes. The generic paradigm is a formal problem called “distributed match-making.” We define multidimensional and weighted versions, and the relations between the two, and develop a very general method to prove lower bounds on the complexity as a tradeoff between number of messages and “distributedness.” The resulting lower bounds are tight in all cases we have examined. We present a success-stop version of distributed match-making that is analysed in terms of a weight distribution that in all cases results in approximately halving the (expected) number of messages required in the corresponding strategy that does not use these weights. The second author did part of this work at the Laboratory for Computer Science, M.I.T., Cambridge, MA. He was supported in part by the Office of Naval Research under Contract N00014-85-K-0168, by the Office of Army Research under Contract DAAG29-84-K-0058, by the National Science Foundation under Grant DCR-83-02391, and by the Defence Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125. A preliminary version of this paper appeared inProc. VLSI Algorithms and Architectures, 3rd Aegean Workshop on Computing (AWOC 88), Lecture Notes in Computer Science, vol. 319, Springer-Verlag, Berlin, 1988, pp. 361–368.     

An optimal algorithm for shortest paths on weighted interval and circular-arc graphs,with applications

We give the first linear-time algorithm for computing single-source shortest paths in a weighted interval or circular-arc graph, when we are given the model of that graph, i.e., the actual weighted intervals or circular-arcsand the sorted list of the interval endpoints. Our algorithm solves this problem optimally inO(n) time, wheren is the number of intervals or circular-arcs in a graph. An immediate consequence of our result is anO(qn + n logn)-time algorithm for the minimum-weight circle-cover problem, whereq is the minimum number of arcs crossing any point on the circle; then logn term in this time complexity is from a preprocessing sorting step when the sorted list of endpoints is not given as part of the input. The previously best time bounds were0(n logn) for this shortest paths problem, andO(qn logn) for the minimum-weight circle-cover problem. Thus we improve the bounds of both problems. More importantly, the techniques we give hold the promise of achieving similar (logn)-factor improvements in other problems on such graphs.The research of M. J. Atallah was supported in part by the Leonardo Fibonacci Institute, Trento, Italy, by the Air Force Office of Scientific Research under Contract AFOSR-90-0107, and by the National Science Foundation under Grant CCR-9202807. D. Z. Chen's research was supported in part by the Leonardo Fibonacci Institute, Trento, Italy. The research of D. T. Lee was supported in part by the Leonardo Fibonacci Institute, Trento, Italy, by the National Science Foundation, and the Office of Naval Research under Grants CCR-8901815, CCR-9309743, and N00014-93-1-0272.     

Programming simultaneous actions using common knowledge

This work applies the theory of knowledge in distributed systems to the design of efficient fault-tolerant protocols. We define a large class of problems requiring coordinated, simultaneous action in synchronous systems, and give a method of transforming specifications of such problems into protocols that areoptimal in all runs: these protocols are guaranteed to perform the simultaneous actions as soon as any other protocol could possibly perform them, given the input to the system and faulty processor behavior. This transformation is performed in two steps. In the first step we extract, directly from the problem specification, a high-level protocol programmed using explicit tests for common knowledge. In the second step we carefully analyze when facts become common knowledge, thereby providing a method of efficiently implementing these protocols in many variants of the omissions failure model. In the generalized omissions model, however, our analysis shows that testing for common knowledge is NP-hard. Given the close correspondence between common knowledge and simultaneous actions, we are able to show that no optimal protocol for any such problem can be computationally efficient in this model. The analysis in this paper exposes many subtle differences between the failure models, including the precise point at which this gap in complexity occurs.This research was supported by the Office of Naval Research under contract N00014-85-K-0168, by the Office of Army Research under contract DAAG29-84-K-0058, by the National Science Foundation under Grant DCR-8302391, and by the Defense Advanced Research Projects agency (DARPA) under contract N00014-83-K-0125, and was performed while both authors were at MIT. A preliminary version of this work appeared in theProceedings of the 27th Annual IEEE Symposium on Foundations of Computer Science, Toronto, 1986.This author was primarily supported by an IBM postdoctoral fellowship.     

Augmented infinitesimal perturbation analysis: An alternate explanation

Augmented infinitesimal perturbation analysis (APA) was introduced by Gaivoronski [1991] to increase the purview of the theory of Infinitesimal Perturbation Analysis (IPA). In reference [Gaivoronski 1991] it is shown that an unbiased estimate for the gradient of a class of performance measures of DEDS represented bygeneralized semi-Markov processes (GSMPs) (cf. [Glynn 1989] can be expressed as a sum of an IPA-estimate and a term that takes into account the event order changes. In this paper we present an alternate approach to establishing the result of Gaivoronski, and from this we derive a necessary and sufficient condition for the validity of the IPA algorithm for this class of performance measures. Finally we validate our results by simulation examples.This research was supported by the National Science Foundation under grant number ECS-85-15449, Office of Naval Research Grants Nos. N00014-90-K-1093 and N00014-89-J-1023 and by Army Grant No. DAAL-03-86-K-0171.     

Selecting distances in the plane

We present a randomized algorithm for computing the kth smallest distance in a set ofn points in the plane, based on the parametric search technique of Megiddo [Mel]. The expected running time of our algorithm is O(n^4/3 log^8/3 n). The algorithm can also be made deterministic, using a more complicated technique, with only a slight increase in its running time. A much simpler deterministic version of our procedure runs in time O(n^3/2 log^5/2 n). All versions improve the previously best-known upper bound ofO(@#@ n^9/5 log^4/5 n) by Chazelle [Ch]. A simpleO(n logn)-time algorithm for computing an approximation of the median distance is also presented.Part of this work was done while the first two authors were visting DIMACS, Rutgers University, New Brunswick, NJ. Work by the first three authors has been partly supported by Office of Naval Research Grant N00014-87-K-0129, by National Science Foundation Grant DCR-83-20085, and by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center-NSF-STC88-09648. Work by the second author has also been supported by National Security Agency Grant MDA 904-89-H-2030. Work by the third author has also been supported by National Science Foundation Grant CCR-89-01484, and by grants from the U.S.-Israeli Binational Science Foundation, and the Fund for Basic Research administered by the Israeli Academy of Sciences.     

Decentralized detection by a large number of sensors

We consider the decentralized detection problem, in whichN independent, identical sensors transmit a finite-valued function of their observations to a fusion center which then decides which one ofM hypotheses is true. For the case where the number of sensors tends to infinity, we show that it is asymptotically optimal to divide the sensors intoM(M-1)/2 groups, with all sensors in each group using the same decision rule in deciding what to transmit. We also show how the optimal number of sensors in each group may be determined by solving a mathematical programming problem. For the special case of two hypotheses and binary messages the solution simplifies considerably: it is optimal (asymptotically, asN→∞) to have all sensors perform an identical likelihood ratio test, and the optimal threshold is very easy to determine numerically. Research supported by the Army Research Office under Contract DAAG-29-84-K-0005 and by the Office of Naval Research under Contract N00014-84-K-0519.     

How to clear a block: A theory of plans

Problems in commonsense and robot planning are approached by methods adapted from program synthesis research; planning is regarded as an application of automated deduction. To support this approach, we introduce a variant of situational logic, called plan theory, in which plans are explicit objects.A machine-oriented deductive-tableau inference system is adapted to plan theory. Equations and equivalences of the theory are built into a unification algorithm for the system. Frame axioms are built into the resolution rule.Special attention is paid to the derivation of conditional and recursive plans. Inductive proofs of theorems for even the simplest planning problems, such as clearing a block, have been found to require challenging generalizations.This research was supported by the National Science Foundation under Grants DCR-82-14523 and DCR-85-12356, by the Defense Advanced Research Projects Agency under Contract N00039-84-C-0211, by the United States Air Force Office of Scientific Research under Contract AFOSR-85-0383, by the Office of Naval Research under Contract N00014-84-C-0706, by United States Army Research under Contract DAJA-45-84-C-0040, and by a contract from the International Business Machines Corporation.Preliminary versions of parts of this paper were presented at the Eighth International Conference on Automated Deduction, Oxford, England, July 1986, and the Workshop on Planning and Reasoning about Actions, Timberline, Oregon, July 1986.     

The general maximum matching algorithm of micali and vazirani

We give a clear exposition of the algorithm of Micali and Vazirani for computing a maximum matching in a general graph. This is the most efficient algorithm known for general matching. On a graph withn vertices andm edges this algorithm runs inO(n ^1/2 m) time.Work on this paper has been supported by the Office of Naval Research under Contract N00014-85-K-0570 and by the Eastman Kodak Company.