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Danny Dolev

  1. A Fault-Resistant Asynchronous Clock Function.

    Thu, 07/15/2010 - 15:01 — SomNambul
    Authors: Danny Dolev, Ezra N. Hoch, Michael Ben-Or
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    Consider an asynchronous network in a shared-memory environment consisting of
    n nodes. Assume that up to f of the nodes might be Byzantine (n > 12f), where
    the adversary is full-information and dynamic (sometimes called adaptive). In
    addition, the non-Byzantine nodes may undergo transient failures. Nodes advance
    in atomic steps, which consist of reading all registers, performing some
    calculation and writing to all registers.

  2. Simple Gradecast Based Algorithms.

    Thu, 07/08/2010 - 15:01 — SomNambul
    Authors: Danny Dolev, Ezra N. Hoch, Michael Ben-Or
    Subjects: and Cluster Computing, Distributed, Parallel
    Abstract

    Gradecast is a simple three-round algorithm presented by Feldman and Micali.
    The current work presents a very simple algorithm that utilized Gradecast to
    achieve Byzantine agreement. Two small variations of the presented algorithm
    lead to improved algorithms for solving the Approximate agreement problem and
    the Multi-consensus problem.

    An optimal approximate agreement algorithm was presented by Fekete, which
    supports up to 1/4 n Byzantine nodes and has message complexity of O(n^k),
    where n is the number of nodes and k is the number of rounds.

  3. Distributed Sensor Selection using a Truncated Newton Method.

    Fri, 01/15/2010 - 16:01 — SomNambul
    Authors: Danny Bickson, Danny Dolev
    Subjects: Information Theory
    Abstract

    We propose a new distributed algorithm for computing a truncated Newton
    method, where the main diagonal of the Hessian is computed using belief
    propagation. As a case study for this approach, we examine the sensor selection
    problem, a Boolean convex optimization problem. We form two distributed
    algorithms. The first algorithm is a distributed version of the interior point
    method by Joshi and Boyd, and the second algorithm is an order of magnitude
    faster approximation. As an example application we discuss distributed anomaly
    detection in networks.

  4. Distributed Fault Identification via Non-parametric Belief Propagation.

    Mon, 08/17/2009 - 18:30 — SomNambul
    Authors: Danny Bickson, Harel Avissar, Danny Dolev, Stephen P. Boyd, Alex T. Ihler, Dror Baron
    Subjects: Information Theory
    Abstract

    We consider the problem of estimating a pattern of faults, represented as a
    binary vector, from a set of measurements. Maximum a posteriori probability
    (MAP) estimation of the fault pattern leads to a difficult combinatorial
    optimization problem. Following recent success of the belief propagation
    framework in the related compressive sensing and low density lattice decoding
    domains, we propose a novel relaxation of the problem using non-parametric
    belief propagation (NBP) for creating a distributed solution.

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