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Yayın Force-directed approaches to sensor localization(SIAM, 2006) Efrat, Alon; Forrester, David; Iyer, Anand; Kobourov, Stephen G.; Erten, CesimWe consider the centralized, anchor-free sensor localization problem. We consider the case where the sensor network reports range information and the case where in addition to the range, we also have angular information about the relative order of each sensor's neighbors. We experimented with classic and new force-directed techniques. The classic techniques work well for small networks with nodes distributed in simple regions. However, these techniques do not scale well with network size and yield poor results with noisy data. We describe a new force-directed technique, based on a multi-scale dead-reckoning, that scales well for large networks, is resilient under range errors, and can reconstruct complex underlying regions.Yayın A robust localization framework to handle noisy measurements in wireless sensor networks(IEEE, 2009-09-14) Erten, Cesim; Karataş, ÖmerWe construct a robust localization framework to handle noisy measurements in wireless sensor networks. Traditionally many approaches employ the distance information gathered from ranging devices of the sensor nodes to achieve localization. However the measurements of these devices may contain noise both as hardware noise and as environmental noise due to the employment conditions of the network. It Is necessary to provide a general framework that handles such a noise in data and yet still be applicable within several localization algorithms. In order to handle noise in distance measurements, our framework utilizes convex constraints and confidence intervals of a random variable. At the end of the localization process nodes are assigned to a set of feasible regions with corresponding probabilities. The accuracy of the localization can be adjusted and the framework can easily be embedded to work within previously suggested localization algorithms.
