A principal consideration for industrial control networks, where the monitoring and control of real-life processes must often occur quickly and at set times, is the guaranteed maximum communication time from one node to another. If you’re controlling the position of a nuclear reactor coolant valve with a digital network, you need to be able to guarantee that the valve’s network node will receive the proper positioning signals from the control computer at the right times. If not, very bad things could happen!
The ability for a network to guarantee data “throughput” is called determinism
. A deterministic network has a guaranteed maximum time delay for data transfer from node to node, whereas a non-deterministic network does not. The preeminent example of a non-deterministic network is Ethernet, where the nodes rely on random time-delay circuits to reset and re-attempt transmission after a collision. Being that a node’s transmission of data could be delayed indefinitely from a long series of re-sets and re-tries after repeated collisions, there is no guarantee that its data will ever
get sent out to the network. Realistically though, the odds are so astronomically great that such a thing would happen that it is of little practical concern in a lightly-loaded network.
Another important consideration, especially for industrial control networks, is network fault tolerance: that is, how susceptible is a particular network’s signaling, topology, and/or protocol to failures? We’ve already briefly discussed some of the issues surrounding topology, but protocol impacts reliability just as much. For example, a Master/Slave network, while being extremely deterministic (a good thing for critical controls), is entirely dependent upon the master node to keep everything going (generally a bad thing for critical controls). If the master node fails for any reason, none of the other nodes will be able to transmit any data at all, because they’ll never receive their alloted time slot permissions to do so, and the whole system will fail.
A similar issue surrounds token-passing systems: what happens if the node holding the token were to fail before passing the token on to the next node? Some token-passing systems address this possibility by having a few designated nodes generate a new token if the network is silent for too long. This works fine if a node holding the token dies, but it causes problems if part of a network falls silent because a cable connection comes undone: the portion of the network that falls silent generates its own token after awhile, and you essentially are left with two smaller networks with one token that’s getting passed around each of them to sustain communication. Trouble occurs, however, if that cable connection gets plugged back in: those two segmented networks are joined in to one again, and now there’s two tokens being passed around one network, resulting in nodes’ transmissions colliding!
There is no “perfect network” for all applications. The task of the engineer and technician is to know the application and know the operations of the network(s) available. Only then can efficient system design and maintenance become a reality.