Network Boundary Identification using Local Information

Abstract

Detection of nodes on the network boundary is necessary for correct operation in many wireless applications. Many virtual coordinate constructions rely on the furthest set of nodes as beacons, and sensing applications may find useful the knowledge of the network edge. In this paper we propose local convex view (lcv) as a means to identify nodes close to the network edge. It is based on the idea that -hulls can capture the shape of a set of points, and motivated by the hypothesis that some structural information relevant to the network is buried within view of many nodes. The lcv differs from most previous methods in that it is a localized algorithm. Nodes using lcv establish neighbourhood coordinates where no location information is available a priori. In those cases where needed information is missing, we adopt a simple probabilistic model to decide the boundary status of a node. We identify two metrics for evaluation, and compare via simulation the performance of lcv against two methods with similar properties. In our experiments we find lcv to be consistent in its performance, and resilient to the impediments facing other methods.