Selection of Mobile Edges for a Hybrid CrowdSensing Architecture
Dimitri Belli, Stefano Chessa, Antonio Corradi, Giampiero Di Paolo, Luca Foschini, Michele Girolami · 2019
Mobile crowdsensing aims at the collection of sensor data on the environment by leveraging personal devices, usually smartphones. Its popularity is due to the ability of reaching capillary even the most remote areas (provided humans live there), with no infrastructure costs. This is possible because it leverages on existing 4G/5G communication infrastructures that are now rapidly evolving towards edge computing models. In this work we address the synergy between mobile crowdsensing and multi-access edge computing by analysing and assessing strategies for the selection of fixed and mobile edges to support the collection of mobile crowdsensing data.