Analytical Characterization of Computationally Efficient Localization Techniques
Trilateration-based localization techniques have been widely used in sensor networks due to their computational efficiency and distributedness. However in sparse networks or in the boundary area of networks, trilateration-based techniques often fail to localize all localizable nodes. Bilateration-based techniques emerge as a generalization of trilateration techniques to a broader class of networks. Compared with trilateration-based techniques, the main benefit of bilateration-based schemes is that they can localize a higher percentage of nodes while still maintaining the low computational complexity and distributedness properties. One potential drawback of bilaterationbased schemes is that the number of estimated possible positions (hence the memory required to store these positions) may grow exponentially with the number of nodes in the network.