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Michael T. Goodrich

Researcher at University of California, Irvine

Publications -  445
Citations -  14652

Michael T. Goodrich is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Planar graph & Time complexity. The author has an hindex of 61, co-authored 430 publications receiving 14045 citations. Previous affiliations of Michael T. Goodrich include New York University & Technion – Israel Institute of Technology.

Papers
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Journal ArticleDOI

Communication-Efficient Parallel Sorting

TL;DR: The bound on the number of communication rounds is asymptotically optimal for the full range of values for p, for it is shown that just computing the "or" of n bits distributed evenly to the first O(n/h) of an arbitrary number of processors in a BSP computer requires $\Omega(\log n/\log (h+1))$ communication rounds.
Journal ArticleDOI

Probabilistic packet marking for large-scale IP traceback

TL;DR: An approach to IP traceback based on the probabilistic packet marking paradigm, which is called randomize-and-link, uses large checksum cords to ldquolinkrdquo message fragments in a way that is highly scalable, for the checksums serve both as associative addresses and data integrity verifiers.
Book ChapterDOI

An Efficient Dynamic and Distributed Cryptographic Accumulator

TL;DR: An accumulator-based scheme for authenticated dictionaries that supports efficient incremental updates of the underlying set by insertions and deletions of elements and can optimally verify in constant time the authenticity of the answer provided by a directory with a simple and practical algorithm.
Proceedings ArticleDOI

Fundamental parallel algorithms for private-cache chip multiprocessors

TL;DR: This paper presents two sorting algorithms, a distribution sort and a mergesort, and studies sorting lower bounds in a computational model, which is called the parallel external-memory (PEM) model, that formalizes the essential properties of the algorithms for private-cache CMPs.
Journal ArticleDOI

A multi-dimensional approach to force-directed layouts of large graphs

TL;DR: A novel hierarchical force-directed method for drawing large graphs that can draw graphs with tens of thousands of vertices using a negligible amount of memory in less than one minute on a 550 MHz Pentium PC.