Proceedings ArticleDOI
Tight bounds for minimax grid matching, with applications to the average case analysis of algorithms
Frank Thomson Leighton,Peter W. Shor +1 more
- pp 91-103
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TLDR
The minimax grid matching problem is a fundamental combinatorial problem associated with the average case analysis of algorithms that is best known for its application to the maximum up-right matching problem.Abstract:
The minimax grid matching problem is a fundamental combinatorial problem associated with the average case analysis of algorithms. The problem has arisen in a number of interesting and seemingly unrelated areas, including wafer-scale integration of systolic arrays, two-dimensional discrepancy problems, and testing pseudorandom number generators. However, the minimax grid matching problem is best known for its application to the maximum up-right matching problem. The maximum up-right matching problem was originally defined by Karp, Luby and Marchetti-Spaccamela in association with algorithms for 2-dimensional bin packing. More recently, the up-right matching problem has arisen in the average case analysis of on-line algorithms for 1-dimen-sional bin packing and dynamic allocation.read more
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Review: Coverage and connectivity issues in wireless sensor networks: A survey
Amitabha Ghosh,Sajal K. Das +1 more
TL;DR: Several state-of-the-art algorithms and techniques are presented and compared that aim to address the coverage-connectivity issue in wireless sensor networks.
Proceedings ArticleDOI
Data fusion improves the coverage of wireless sensor networks
TL;DR: The scaling laws between coverage, network density, and signal-to-noise ratio (SNR) are derived and it is shown that data fusion can significantly improve sensing coverage by exploiting the collaboration among sensors.
Proceedings ArticleDOI
Trade-offs between mobility and density for coverage in wireless sensor networks
TL;DR: This paper proposes a distributed relocation algorithm, where each mobile sensor only requires local information in order to optimally relocate itself and characterize the algorithm's computational complexity and message overhead.
Journal ArticleDOI
Error Estimates for Spectral Convergence of the Graph Laplacian on Random Geometric Graphs Toward the Laplace–Beltrami Operator
TL;DR: The convergence of the graph Laplacian of a random geometric graph generated by an i.i.d. sample from a m-dimensional submanifold was studied in this paper.
References
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Wafer-Scale Integration of Systolic Arrays
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