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Anchor-Free Distributed Localization in Sensor Networks
A fully decentralized algorithm called AFL (Anchor-Free Localization) where nodes start from a random initial coordinate assignment and converge to a consistent solution using only local node interactions, which is superior to previously proposed methods that incrementally compute the coordinates of nodes in the network.
PSPACE-completeness of sliding-block puzzles and other problems through the nondeterministic constraint logic model of computation
Correlation clustering in general weighted graphs
Representing Trees of Higher Degree
- David Benoit, E. Demaine, J. I. Munro, R. Raman, Venkatesh Raman, S. S. Rao
- Computer ScienceAlgorithmica
- 1 December 2005
These representations use a number of bits close to the information theoretic lower bound and support operations in constant time, giving unique labels to the nodes of the tree, which can be used to store satellite information with the nodes efficiently.
Frequency Estimation of Internet Packet Streams with Limited Space
An algorithm that deterministically finds (in particular) all categories having a frequency above 1/(m+1) using m counters, which it is proved is best possible in the worst case and best possible up to a logarithmic factor.
- M. A. Bender, E. Demaine, Martin Farach-Colton
- Computer ScienceProceedings 41st Annual Symposium on Foundations…
- 12 November 2000
We present dynamic search-tree data structures that perform well in the setting of a hierarchical memory (including various levels of cache, disk, etc.), but do not depend on the number of memory…
Deploying sensor networks with guaranteed capacity and fault tolerance
This work designs and analyzes the first algorithms that place an almost-minimum number of additional sensors to augment an existing network into a k-connected network, for any desired parameter k, and proves that the number ofAdditional sensors is within a constant factor of the absolute minimum for any fixed k.
Geometric folding algorithms - linkages, origami, polyhedra
Aimed primarily at advanced undergraduate and graduate students in mathematics or computer science, this lavishly illustrated book will fascinate a broad audience, from high school students to researchers.
Adaptive set intersections, unions, and differences
This work develops a framework for designing and evaluating adaptive algorithms in the comparison model, and presents adaptive algorithms that make no a priori assumptions about the problem instance, and show that their running times are within a constant factor of optimal with respect to a natural measure of the difficulty of an instance.