Abstract
The development of vehicular technologies and infrastructures leads to development in mobility handling for wireless communications. Improving connectivity establishment and reliability became an issue, especially for vehicles that may move out of antenna coverage during connection establishment. This paper focuses on improving LoRaWAN connectivity for roaming devices by combining a machine learning predictor and DNS prefetching to gather information necessary for connection establishment before the device comes under coverage, thus reducing the overall latency for connection establishment. The paper also relates to other issues by comparing the solution with other approaches and studying antenna occupation.
“Prefetching of mobile devices information - a DNS perspective” introduces a method to reduce network connection times in roaming contexts using a traffic trend predictor.
Deep learning algorithms predict traffic trajectories, which are then used in a simulator to estimate time savings achieved by combining prefetching and DNS-based information caching mechanisms.
A longer version of this article is on the way for a journal article.
Antoine BERNARD
Postdoctoral Fellow @ Polytechnique Montréal
Tech enthousiast, interested in computer networks, distributed processing and a bit of AI.