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The K-Neigh Protocol for Symmetric Topology Control in Ad Hoc Networks
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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
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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
Efficient algorithms for distributed detection of holes and boundaries in wireless networks
SEA'11 Proceedings of the 10th international conference on Experimental algorithms
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Robotics and Autonomous Systems
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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 article tackles the challenge of providing a scalable and range-free solution for boundary recognition that does not require a high node density. We explain the challenges of accurately defining the boundary of a wireless sensor network with and without node positions and provide a new definition of network boundary in the discrete domain. Our solution for boundary recognition approximates the boundary of the sensor network by determining the majority of inner nodes using geometric constructions, which 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 present a fully distributed algorithm for boundary recognition based on these concepts and perform a detailed complexity analysis. We provide a thorough evaluation of our approach and show that it is applicable to dense as well as sparse deployments.