Path planning and localization for mobile anchor based wireless sensor networks

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2017
Erdemir, Ecenaz
In wireless sensor networks, sensors with limited resources are distributed in a wide area. Localizing the sensors is an important problem. Anchor nodes with known positions are used for sensor localization. A simple and efficient way of generating anchor nodes is to use mobile anchors which have built-in GPS units. In this thesis, a single mobile anchor is used to traverse the region of interest to communicate with the sensor nodes and identify their positions. Therefore planning the best trajectory for the mobile anchor is an important problem in this context. The mobile anchor stops on the trajectory to generate anchor nodes which are used in the position estimation of the unknown sensors. Various path planning methods for mobile anchors are proposed to localize as many sensors as possible by following the shortest path with minimum number of anchors. In this thesis, path planning and localization for mobile anchor based wireless sensor networks are investigated. Two novel path planning algorithms are proposed for static and dynamic schemes. These approaches use mobile anchors to cover the monitoring area with minimum path length and by stopping at minimum number of nodes. Moreover, alternating minimization algorithm is proposed for localizing the unknown sensor nodes non-cooperatively. The non-convex, NP-hard node localization problem is converted into a biconvex form and solved iteratively. The performances of the proposed path planning algorithms are compared with alternative approaches through simulations. The results show that more sensors are localized with less anchors in a shorter path and time for both schemes. Furthermore, alternating minimization algorithm provides an effective solution for the sensor localization problem. The simulation results show that the proposed localization approach is less prone to error accumulation than the alternative methods. 
Citation Formats
E. Erdemir, “Path planning and localization for mobile anchor based wireless sensor networks,” M.S. - Master of Science, 2017.