  The trend of future communication systems is to aim for the steering and
control of cyber physical systems. These systems can quickly become congested
in environments like those presented in Industry 4.0. In these scenarios, a
plethora of sensor data is transmitted wirelessly to multiple in network
controllers that compute the control functions of the cyber physical systems.
In this paper, we show an implementation of network Functional Compression (FC)
as a proof of concept to drastically reduce the data traffic in these
scenarios. FC is a form of goal-oriented communication scheme in which the
objective of the sender receiver pair is to transmit the minimum amount of
information to compute a function at the receiver end. In our scenario, the
senders transmit an encoded and compressed version of the sensor data to a
destination, an in-network controller interested in computing as its target
function, a PID controller. We show that it is possible to achieve compression
rates of over 50% in some cases by employing FC. We also show that using FC in
a distributed cascade fashion can achieve more significant compression rates
while reducing computational costs.
