Data networks (2nd ed.)
Approximation schemes for covering and packing problems in image processing and VLSI
Journal of the ACM (JACM)
NC-approximation schemes for NP- and PSPACE-hard problems for geometric graphs
Journal of Algorithms
Polynomial-time approximation schemes for geometric graphs
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Approximation algorithms
Minimum-cost coverage of point sets by disks
Proceedings of the twenty-second annual symposium on Computational geometry
The coverage problem in a wireless sensor network
Mobile Networks and Applications
Bounds on coverage and target detection capabilities for models of networks of mobile sensors
ACM Transactions on Sensor Networks (TOSN)
On clustering to minimize the sum of radii
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Polynomial time approximation schemes for base station coverage with minimum total radii
Computer Networks: The International Journal of Computer and Telecommunications Networking
Geometric clustering to minimize the sum of cluster sizes
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Maximizing network lifetime on the line with adjustable sensing ranges
ALGOSENSORS'11 Proceedings of the 7th international conference on Algorithms for Sensor Systems, Wireless Ad Hoc Networks and Autonomous Mobile Entities
More is more: The benefits of denser sensor deployment
ACM Transactions on Sensor Networks (TOSN)
Brief announcement: set it and forget it - approximating the set once strip cover problem
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
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We consider dual classes of geometric coverage problems, in which disks, corresponding to coverage regions of sensors, are used to cover a region or set of points in the plane. The first class of problems involve assigning radii to already-positioned sensors (being cheap ). The second class of problems are motivated by the fact that the sensors may, because of practical difficulties, be positioned with only approximate accuracy (being flexible ). This changes the character of some coverage problems that solve for optimal disk positions or disk sizes, ordinarily assuming the disks can be placed precisely in their chosen positions, and motivates new problems. Given a set of disk sensor locations, we show for most settings how to assign either (near-)optimal radius values or allowable amounts of placement error. Our primary results are 1) in the 1-d setting we give a faster dynamic programming algorithm for the (linear) sensor radius problem; and 2) we find a max-min fair set of radii for the 2-d continuous problems in polynomial time. We also give results for other settings, including fast approximation algorithms for the 1-d continuous case.