Asymptotically optimal algorithms for approximate agreement

This paper introduces some algorithms to solve crash-failure, failure-by-omission and Byzantine failure versions of the Byzantine Generals or consensus problem, where non-faulty processors need only arrive at values that are close together rather than identical. For each failure model and each value ofS, we give at-resilient algorithm usingS rounds of communication. IfS=t+1, exact agreement is obtained. In the algorithms for the failure-by-omission and Byzantine failure models, each processor attempts to identify the faulty processors and corrects values transmited by them to reduce the amount of disagreement. We also prove lower bounds for each model, to show that each of our algorithms has a convergence rate that is asymptotic to the best possible in that model as the number of processors increases. Alan Fekete was born in Sydney Australia in 1959. He studied Pure Mathematics and Computer Science at the University of Sydney, obtaining a B.Sc.(Hons) in 1982. He then moved to Cambridge, Massachusetts, where he obtained a distributed Ph.D. degree, awarded by Harvard University's Mathematics department for work supervised by Nancy Lynch in M.I.T.'s Laboratory for Computer Science. He spend the year 1987–1988 at M.I.T. as a postdoctoral Research Associate, and is now Lecturer in Computer Science at the University of Sydney. His research concentrates on understanding the modularity in distributed algorithms, especially those used for concurrency control in distributed databases.A preliminary version of this paper has appeared in the Proceedings of the 5th ACM Symposium on Principles of Distributed Computing (August 1986). This work was begun in the Department of Mathematics, Harvard University, and completed at the Laboratory for Computer Science at Massachusetts Institute of Technology. The work was supported in part (through Professor N. Lynch) 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 Grants MCS-8306854, DCR-83-02391, and CCR-8611442, and by the Defense Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125     

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.     

Efficient comparison of program slices

Theslice of a program with respect to a componentc is a projection of the program that includes all components that might affect (either directly or transitively) the values of the variables used atc. Slices can be extracted particularly easily from a program representation called a program dependence graph, originally introduced as an intermediate program representation for performing optimizing, vectorizing, and parallelizing transformations. This paper presents a linear-time algorithm for determining whether two slices of a program dependence graph are isomorphic.This work was supported in part by a David and Lucile Packard Fellowship for Science and Engineering, by the National Science Foundation under grants DCR-8552602 and CCR-8958530, by the Defense Advanced Research Projects Agency, monitored by the Office of Naval Research under contract N00014-88-K-0590, and by grants from IBM, DEC, Xerox, 3M, Eastman Kodak, and the Cray Research Foundation.     

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.     

Optimal parallel verification of minimum spanning trees in logarithmic time

We present the first optimal parallel algorithms for the verification and sensitivity analysis of minimum spanning trees. Our algorithms are deterministic and run inO(logn) time and require linear-work in the CREW PRAM model. These algorithms are used as a subroutine in the linear-work randomized algorithm for finding minimum spanning trees of Cole, Klein, and Tarjan. Research partially supported by a National Science Foundation Graduate Fellowship and by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center, Grant No. NSF-STC88-09648. Research at Princeton University was partially supported by the National Science Foundation, Grant No. CCR-8920505, the Office of Naval Research, Contract No. N00014-91-J-1463, and by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), a National Science Foundation Science and Technology Center, Grant No. NSF-STC88-09648.     

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.     

The complexity of planar compliant motion planning under uncertainty

We consider the computational complexity of planning compliant motions in the plane, given geometric bounds on the uncertainty in sensing and control. We can give efficient algorithms for generating and verifying compliant motion strategies that are guaranteed to succeed as long as the sensing and control uncertainties lie within the specified bounds. We also consider the case where a compliant motion plan is required to succeed over some parametric family of geometries. While these problems are known to be intractable in three dimensions, we identify tractable subclasses in the plane.This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory's Artificial Intelligence research is provided in part by the Office of Naval Research under Office of Naval Research Contract N00014-81-K-0494 and in part by the Advanced Research Projects Agency under Office of Naval Research Contracts N00014-85-K-0124 and N00014-82-K.-0334. The author was funded in part by a NASA fellowship administered by the Jet Propulsion Laboratory, and in part by the Mathematical Sciences Institute and the National Science Foundation.     

Fast algorithms for bit-serial routing on a hypercube

In this paper we describe anO(logN)-bit-step randomized algorithm for bit-serial message routing on a hypercube. The result is asymptotically optimal, and improves upon the best previously known algorithms by a logarithmic factor. The result also solves the problem of on-line circuit switching in anO(1)-dilated hypercube (i.e., the problem of establishing edge-disjoint paths between the nodes of the dilated hypercube for any one-to-one mapping).Our algorithm is adaptive and we show that this is necessary to achieve the logarithmic speedup. We generalize the Borodin-Hopcroft lower bound on oblivious routing by proving that any randomized oblivious algorithm on a polylogarithmic degree network requires at least (log² N/log logN) bit steps with high probability for almost all permutations.This research was supported by the Defense Advanced Research Projects Agency under Contracts N00014-87-K-825 and N00014-89-J-1988, the Air Force under Contract AFOSR-89-0271, and the Army under Contract DAAL-03-86-K-0171. This work was completed while the third and fourth authors were at the Laboratory for Computer Science, Massachusetts Institute of Technology.     

Planar geometric location problems

We present anO(n ² log³ n) algorithm for the two-center problem, in which we are given a setS ofn points in the plane and wish to find two closed disks whose union containsS so that the larger of the two radii is as small as possible. We also give anO(n ² log⁵ n) algorithm for solving the two-line-center problem, where we want to find two strips that coverS whose maximum width is as small as possible. The best previous solutions of both problems requireO(n ³) time.Pankaj Agarwal has been supported by DIMACS (Center for Discrete Mathematics and Theoretical Computer Science), an NSF Science and Technology Center, under Grant STC-88-09648. Micha Sharir has been supported by the Office of Naval Research under Grants N00014-89-J-3042 and N00014-90-J-1284, by the National Science Foundation under Grant CCR-89-01484, by DIMACS, and by grants from the US-Israeli Binational Science Foundation, the Fund for Basic Research administered by the Israeli Academy of Sciences, and the G.I.F., the German-Israeli Foundation for Scientific Research and Development. A preliminary version of this paper has appeared inProceedings of the Second Annual ACM-SIAM Symposium on Discrete Algorithms, 1991, pp. 449–458.     

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.     

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.     

Highly concurrent logically synchronous multicast

We define thelogically synchronous multicast problem which imposes a natural and useful structure on message delivery order in an asynchronous system. In this problem, a computation proceeds by a sequence ofmulticasts, in which a process sends a message to some arbitrary subset of the processes, including itself. A logically synchronous multicast protocol must make it appear to every process as if each multicast occurs simultaneously at all participants of that multicast (sender plus receivers). Furthermore, if a process continually wishes to send a message, it must eventually be permitted to do so.We present a highly concurrent solution in which each multicast requires at most 4|S| messages, whereS is the set of participants in that multicast. The protocol's correctness is shown using a careful problem specification stated in the I/O automaton model. We conclude the paper by describing how the logically synchronous multicast protocol can be used for distributed simulation of algorithms expressed as I/O automata. Kenneth J. Goldman received the Sc.B. degree in Computer Science from Brown University in 1984, the S.M. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 1987, and the Ph.D. degree in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology in 1990. As part of his doctoral work, he designed and implemented the Spectrum Simulation System, a distributed algorithm development tool based on the I/O automaton model of Lynch and Tuttle. His publications include papers in the areas of models for distributed computing, database concurrency control, human interfaces, and image processing. He is currently Assistant Professor in the Department of Computer Science at Washington University in St. Louis.A preliminary version of this paper appeared in the Proceedings of the 3rd International Workshop on Distributed Algorithms, Lecture Notes in Computer Science 392, Bermond and Raynal, Eds., Springer-Verlag, Berlin, 1989, pp 94–109.This research was conducted at the Massachusetts Institute of Technology Laboratory for Computer Science and was supported in part by the National Science Foundation under Grant CCR-86-11442, by the Office of Naval Research under Contract N00014-85-K-0168, by the Defense Advanced Research Projects Agency (DARPA) under Contract N00014-83-K-0125, and by an Office of Naval Research graduate fellowship     

On the recognition of parameterized 2D objects

Determining the identity and pose of oceluded objects from noisy data is a critical step in interacting intelligently with an unstructured environment. Previous work has shown that local measurements of position and surface orientation may be used in a constrained search process to solve this problem, for the case of rigid objects, either two-dimensional or three-dimensional. This paper considers the more general problem of recognizing and locating objects that can vary in parameterized ways. We consider two-dimensional objects with rotational, translational, or scaling degrees of freedom, and two-dimensional objects that undergo stretching transformations. We show that the constrained search method can be extended to handle the recognition and localization of such generalized classes of object families.This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by an Office of Naval Research University Research Initiative grant under contract N00014-86-K-0180, in part by the Advanced Research Projects Agency of the Department of Defense under Army contract number DACA76-85-C-0010, and in part by DARPA under. Office of Naval Research contract N00014-85-K-0124. A preliminary version of this work appeared in the proceedings of the First International Conference on Computer Vision, London, England, 1987.     

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.     

A formalization of priority inversion

A priority inversion occurs when a low-priority task causes the execution of a higher-priority task to be delayed. The possibility of priority inversions complicates the analysis of systems that use priority-based schedulers because priority inversions invalidate the assumption that a task can be delayed by only higher-priority tasks. This paper formalizes priority inversion and gives sufficient conditions as well as some new protocols for preventing priority inversions.Supported by the Commission of the European Communities under the ESPRIT Programme Basic Research Action Number 3092 (Predictably Dependable Computing Systems) and the Italian Ministry of Research and University, and in part by the Defense Advanced Research Projects Agency (DoD) under NASA Ames grant number NAG-2-593.Supported in part by the Defense Advanced Research Projects Agency (DoD) under NASA Ames grant number NAG 2-593, and by grants from IBM T.J. Watson Research Laboratory, the IBM Endicott Programming Laboratory, Siemens RTL, and Xerox Webster Research Center.Supported in part by the Office of Naval Research under contract N00014-91-J-1219, the National Science Foundation under Grant No. CCR-8701103, DARPA/NSF Grant No. CCR-9014363, and by the IBM Endicott Programming Laboratory.     

Lazy structure sharing for query optimization

We studylazy structure sharing as a tool for optimizing equivalence testing on complex data types. We investigate a number of strategies for implementing lazy structure sharing and provide upper and lower bounds on their performance (how quickly they effect ideal configurations of our data structure). In most cases when the strategies are applied to a restricted case of the problem, the bounds provide nontrivial improvements over the naïve linear-time equivalence-testing strategy that employs no optimization. Only one strategy, however, which employs path compression, seems promising for the most general case of the problem.Work completed while at Princeton University and supported by a Fannie and John Hertz Foundation Fellowship, National Science Foundation Grant No. CCR-8920505, and the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) under NSF-STC-91-19999.Work completed while at Princeton University and DIMACS and supported by DIMACS under NSF-STC-91-19999.Research at Princeton University partially supported by the National Science Foundation, Grant No. CCR-8920505, the Office of Naval Research, Contract No. N00014-91-J-1463, and by DIMACS under NSF-STC-91-19999.     

Dynamic expression trees

We present a technique for dynamically maintaining a collection of arithmetic expressions represented by binary trees (whose leaves are variables and whose internal nodes are operators). A query operation asks for the value of an expression (associated with the root of a tree). Update operations include changing the value of a variable and combining or decomposing expressions by linking or cutting the corresponding trees. Our dynamic data structure uses linear space and supports queries and updates in logarithmic time. An important application is the dynamic maintenance of maximum flow and shortest path in series-parallel digraphs under a sequence of vertex and edge insertions, series and parallel compositions, and their respective inverses. Queries include reporting the maximum flow or shortestst-path in a series-parallel subgraph.Research supported in part by the National Science Foundation under Grant CCR-9007851, by the US Army Research Office under Grants DAAL03-91-G-0035 and DAAH04-93-0134, by the Office of Naval Research and the Defense Advanced Research Projects Agency under Contract N00014-91-J-4052, ARPA Order 8225, and by Cadre Technologies, Inc.     

On multiple moving objects

This paper explores the motion-planning problem for multiple moving objects. The approach taken consists of assigning priorities to the objects, then planning motions one object at a time. For each moving object, the planner constructs a configuration space-time that represents the time-varying constraints imposed on the moving object by the other moving and stationary objects. The planner represents this space-time approximately, using two-dimensional slices. The space-time is then searched for a collision-free path. The paper demonstrates this approach in two domains. One domain consists of translating planar objects; the other domain consists of two-link planar articulated arms.This report describes research performed at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Michael Erdmann is supported in part by a fellowship from General Motors Research Laboratories. Tomás Lozano-Pérez is supported by an NSF Presidential Young Investigator grant. Support for the Laboratory's Artificial Intelligence research is provided in part by the System Development Foundation, in part by the Office of Naval Research under Office of Naval Research Contract N00014-81-K-0494, and in part by the Advanced Research Projects Agency under Office of Naval Research Contracts N00014-80-C-0505 and N00014-82-K-0344.     

Action transducers and timed automata

Thetimed automaton model of [LyV92, LyV93] is a general model for timing-based systems. A notion oftimed action transducer is here defined as an automata-theoretic way of representing operations on timed automata. It is shown that two timed trace inclusion relations are substitutive with respect to operations that can be described by timed action transducers. Examples are given of operations that can be described in this way, and a preliminary proposal is given for an appropriate language of operators for describing timing-based systems.A preliminary version of this paper appeared in W.R. Cleaveland, editor,Proceedings CONCUR'92, Stony Brook, New York. LNCS 630, pages 436–455. Springer, 1992.Supported by ONR contracts N00014-85-K-0168 and N00014-91-J-1988, by NSF grant CCR-8915206, and by ARPA contracts N00014-89-J-1988 and N00014-92-J-4033.Supported by ESPRIT BRA 7166 CONCUR2 and by the HCM network EXPRESS. Part of the work on this paper was done while the author was at the Ecole des Mines, CMA, Sophia Antipolis, France, and at CWI, Amsterdam, The Netherlands.     

WorkCrews: An abstraction for controlling parallelism

In implementing parallel programs, it is important to find strategies for controlling parallelism that make the most effective use of available resources. In this paper, we introduce a dynamic strategy called WorkCrews for controlling the use of parallelism on small-scale, tightly-coupled multiprocessors. In the WorkCrew model, tasks are assigned to a finite set ofworkers. As in other mechanisms for specifying parallelism, each worker can enqueue subtasks for concurrent evaluation by other workers as they become idle. The WorkCrew paradigm has two advantages. First, much of the work associated with task division can be deferred until a new worker actually undertakes the subtask and avoided altogether if the original worker ends up executing the subtask serially. Second, the ordering of queue requests under WorkCrews favors coarse-grained subtasks, which reduces further the overhead of task decomposition.Mark Vandevoorde's work in this project was supported in part by the Advanced Research Projects Agency of the Department of Defense, monitored by the Office of Naval Research under contract N00014-83-K-0125; Digital Equipment Corporation's Systems Research Center; the National Science Foundation under Grant 8706652-CCR; and the NYNEX Corporation. Current address: Laboratory for Computer Science, Massachusetts Institute of Technology.Digital Equipment Corporation, Systems Research Center.