Presented herein is a framework for prioritizing location measurements of multiple client devices. In particular, rather than using a round robin scheduling approach, the techniques presented herein utilize a machine learning block (e.g., random forests) to predict a score for each client device, along with a score-based scheduler.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.