Data Caching at Fog Nodes Under IoT Networks: Review of Machine Learning
Approaches
Abstract
IoT devices (wireless sensors, actuators, computer devices) produce
large volume and variety of data and the data
produced by the IoT devices are transient. In order to overcome the
problem of traditional IoT architecture where
data is sent to the cloud for processing, an emerging technology known
as fog computing is proposed recently.
Fog computing brings storage, computing and control near to the end
devices. Fog computing complements the
cloud and provide services to the IoT devices. Hence, data used by the
IoT devices must be cached at the fog nodes
in order to reduce the bandwidth utilization and latency. This chapter
discusses the utility of data caching at the
fog nodes. Further, various machine learning techniques can be used to
reduce the latency by caching the data
near to the IoT devices by predicting their future demands. Therefore,
this chapter also discusses various machine
learning techniques that can be used to extract the accurate data and
predict future requests of IoT devices.