Voronoi diagrams—a survey of a fundamental geometric data structure
ACM Computing Surveys (CSUR)
Order-k Voronoi Diagrams, k-Sections, and k-Sets
JCDCG '98 Revised Papers from the Japanese Conference on Discrete and Computational Geometry
Energy-Optimal and Energy-Balanced Sorting in a Single-Hop Wireless Sensor Network
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Wireless Sensor Networks: An Information Processing Approach
Wireless Sensor Networks: An Information Processing Approach
Exact distributed Voronoi cell computation in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Energy-efficient coverage for target detection in wireless sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Energy-based collaborative source localization using acoustic microsensor array
EURASIP Journal on Applied Signal Processing
On k-Nearest Neighbor Voronoi Diagrams in the Plane
IEEE Transactions on Computers
SFCS '75 Proceedings of the 16th Annual Symposium on Foundations of Computer Science
On the Fermat--Weber center of a convex object
Computational Geometry: Theory and Applications
IEEE Transactions on Signal Processing
On Energy-Based Acoustic Source Localization for Sensor Networks
IEEE Transactions on Signal Processing
Energy-based sensor network source localization via projection onto convex sets
IEEE Transactions on Signal Processing
Hi-index | 35.68 |
Localization of an isotropic source using energy measurements from randomly deployed sensors is considered. In particular,an optimization problem that does not require knowledge of the underlaying energy decay model is proposed, and a condition under which the optimal solution can be computed is given.This condition employs a new geometric construct introduced here,called the sorted order-K Voronoi diagram. We give centralized and distributed algorithms for source localization in this setting.Finally, analytical results and simulations are used to verify the performance of the developed algorithms.