Network-aware positioning in sensor networks
Out of its importance to various applications and services, the geographical location of the sensed event is to be associated with the event itself being reported. Despite the numerous number of localization algorithms proposed, very few of them are really ad-hoc methods that are appropriate for sensor networks. In this paper, our contribution is double-folded. First, we design an experimental framework to evaluate localization methods for sensor networks. We use this framework to evaluate three localization methods: ad-hoc positioning system (APS), multi-dimensional scaling (MDS), and semi-definite programming (SDP). Using this evaluation, we identify five network properties that affect the localization accuracy. Second, we propose an adaptive localization method that we refer to as: network-aware positioning (NAP). NAP starts by assuming known network properties. Given these properties, NAP determines the best localization algorithm to use. Simulation results show that NAP performs the best among the three algorithms under all network conditions
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