To setup efficient wireless mesh networks, it is fundamental to limit the overhead needed to localize a mobile user. A promising approach is to rely on a rendezvous-based location system where the current location of a mobile node is stored at specific nodes called locators. Nevertheless, such a solution has a drawback, which happens when the locator is far from the source---destination shortest path. This results in a triangular location problem and consequently in increased overhead of signaling messages. One solution to prevent this problem would be to place the locator as close as possible to the mobile node. This requires however to predict the mobile node's location at all times. To obtain such information, we define a mobility prediction model (an agenda) that, for each node, specifies the mesh router that is likely to be the closest to the mobile node at specific time periods. The location service that we propose formalizes the integration of the agenda with the management of location servers in a coherent and self-organized fashion. To evaluate the performance of our system compared to traditional approaches, we use two real-life mobility datasets of Wi-Fi devices in the Dartmouth campus and Taxicabs in the bay area of San Francisco. We show that our strategy significantly outperforms traditional solutions; we obtain gains ranging from 39 to 72% compared to the centralized scheme and more than 35% compared to a traditional rendezvous-based solution.