Voronoi diagrams—a survey of a fundamental geometric data structure
ACM Computing Surveys (CSUR)
Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Mobile Communications Handbook
Mobile Communications Handbook
An Incremental Self-Deployment Algorithm for Mobile Sensor Networks
Autonomous Robots
On deriving the upper bound of α-lifetime for large sensor networks
Proceedings of the 5th ACM international symposium on Mobile ad hoc networking and computing
On k-coverage in a mostly sleeping sensor network
Proceedings of the 10th annual international conference on Mobile computing and networking
Worst and Best-Case Coverage in Sensor Networks
IEEE Transactions on Mobile Computing
The holes problem in wireless sensor networks: a survey
ACM SIGMOBILE Mobile Computing and Communications Review
A Delaunay Triangulation Based Method for Wireless Sensor Network Deployment
ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
Localization using boundary sensors: An analysis based on graph theory
ACM Transactions on Sensor Networks (TOSN)
Distributed coordinate-free algorithm for full sensing coverage
International Journal of Sensor Networks
Coverage in wireless ad hoc sensor networks
IEEE Transactions on Computers
Coverage by randomly deployed wireless sensor networks
IEEE Transactions on Information Theory
Location error estimation in wireless ad hoc networks
Ad Hoc Networks
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This paper analyses the probability that randomly deployed sensor nodes triangulate any point within the target area. Its major result is the probability of triangulation for any point given the number of nodes lying up to a specific distance (2 units) from it, employing a graph representation where an edge exists between any two nodes close than 2 units from one another. The expected number of un-triangulated coverage holes, i.e. uncovered areas which cannot be triangulated by adjacent nodes, in a finite target area is derived. Simulation results corroborate the probabilistic analysis with low error, for any node density. These results will find applications in triangulation-based or trilateration-based pointing analysis, or any computational geometry application within the context of triangulation.