MAP: medial axis based geometric routing in sensor networks
Proceedings of the 11th annual international conference on Mobile computing and networking
Efficient Hop ID based Routing for Sparse Ad Hoc Networks
ICNP '05 Proceedings of the 13TH IEEE International Conference on Network Protocols
Hole detection or: "how much geometry hides in connectivity?"
Proceedings of the twenty-second annual symposium on Computational geometry
Coverage and hole-detection in sensor networks via homology
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Boundary recognition in sensor networks by topological methods
Proceedings of the 12th annual international conference on Mobile computing and networking
A practical evaluation of radio signal strength for ranging-based localization
ACM SIGMOBILE Mobile Computing and Communications Review
Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sensor localization in concave environments
ACM Transactions on Sensor Networks (TOSN)
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The capability of a smart digital system heavily depends on the information about its environment. Such information can be acquired by underlying sensor networks. This paper explores the problem of topology mining in sensor networks. We propose a new mechanism, called relative contour, to evaluate topological features of underlying networks, particularly, for boundary recognition and skeleton extraction in an irregular sensor network. We further propose methods to identify boundary and skeleton of the network. The construction of relative contours and follow-up operations are carried out in distributed manner. Simulation results show that our methods perform well with complex topologies.