Unit disk graph recognition is NP-hard
Computational Geometry: Theory and Applications - Special issue on geometric representations of graphs
The K-Neigh Protocol for Symmetric Topology Control in Ad Hoc Networks
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Geographic routing without location information
Proceedings of the 9th annual international conference on Mobile computing and networking
Proceedings of the 2004 joint workshop on Foundations of mobile computing
Topological hole detection in wireless sensor networks and its applications
DIALM-POMC '05 Proceedings of the 2005 joint workshop on Foundations of mobile computing
MAP: medial axis based geometric routing in sensor networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Deterministic boundary recognition and topology extraction for large sensor networks
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Hole detection or: "how much geometry hides in connectivity?"
Proceedings of the twenty-second annual symposium on Computational geometry
Geometry-based reasoning for a large sensor network
Proceedings of the twenty-second annual symposium on Computational geometry
Boundary recognition in sensor networks by topological methods
Proceedings of the 12th annual international conference on Mobile computing and networking
Algorithmic models for sensor networks
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Fine-grained boundary recognition in wireless ad hoc and sensor networks by topological methods
Proceedings of the tenth ACM international symposium on Mobile ad hoc networking and computing
Perimeter discovery in wireless sensor networks
Journal of Parallel and Distributed Computing
Information Sciences: an International Journal
| Hi-index | 0.00 |
Boundary recognition is an important and challenging issue in wireless sensor networks when no coordinates or distances are available. The distinction between inner and boundary nodes of the network can provide valuable knowledge to a broad spectrum of algorithms. This paper tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. Our solution approximates the boundary of the sensor network by determining the inner nodes using geometric constructions that guarantee that, for a given d, a node lies inside of the construction for a d-quasi unit disk graph model of the wireless sensor network. Moreover, such geometric constructions make it possible to compute a guaranteed distance from a node to the boundary. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.