  Recent advances in the Internet of Things (IoT) technologies have enabled the
use of wearables for remote patient monitoring. Wearable sensors capture the
patient's vital signs, and provide alerts or diagnosis based on the collected
data. Unfortunately, wearables typically have limited energy and computational
capacity, making their use challenging for healthcare applications where
monitoring must continue uninterrupted long time, without the need to charge or
change the battery. Fog computing can alleviate this problem by offloading
computationally intensive tasks from the sensor layer to higher layers, thereby
not only meeting the sensors' limited computational capacity but also enabling
the use of local closed-loop energy optimization algorithms to increase the
battery life.
