The illustration shows different types of "real time" types. This posting was inspired by a comment on a previous posting - trying to do some order in several notions of time. First, the term real-time is frequently used in conjunction with event processing. The popular belief is that real-time = very fast, but this is not really what real-time is about. real-time can be thought of a deadline accompanied by a utility function that designates the damage from missing the deadline. In this illustration there are four type of real-time:
(a). Soft Real-Time: there is a sense to react after the deadline, but the utility decreases (maybe fast) and at some point gets to zero - no use to do it at that point, but no damage.
(b). Firm Real-Time: The utility go immediately to zero when the deadline is missed - no use to do it after the deadline, but no damage.
(c). Hard Essential: Missing the deadline - the utility function goes to a constant negative value; there is a constant penalty.
(d). Hard Critical: Missing the deadline - the utility function goes immediately to "minus infinity", means: a catastrophe will happen.
One can, of course, define the real-time utility function differently, and create more variations.
So - Real-time is not about fast, but about missing the dead-line. The linkage is there, if the dead-line is very short (need to react within 1/1000 of a sec), but many dead-lines are longer than that -- seconds, minutes, hours or days - depends on what is needed to react to - e.g. the contract that we have with our local electricity company says that when a problem is reported, they should start fixing it within 2 hours; the deadline for delivery of Pizza (otherwise it is free of charge) in one of our local delivery centers is 40 minutes - so most the world typically does not work in milliseconds.
When talking about "quality of service" measurements they can be either statistical: in 90 percent of the cases, the deadline should be reached, or individual: for all cases the deadline should be reached. Typically there are different scheduling strategies to achieve each of them - for the individual case it is important to have a consistent deterministic reaction, and this is a source of the various implementations of Real-Time Java - since Java is non deterministic by its nature of garbage collection that happens in undetermined times and lasts for undetermined duration, which may work for the statistical case, but not for the individual case. The Real-Time Java does not stand for Java which runs much faster, but for Java in which the garbage collection differences are smoothed, thus its reaction is (more) deterministic.
What other measurements are there ? in event processing - latency can be measured by the end-to-end (from the time that the event happens in reality to the action being taken in reality), can be related only to the event processing part (from the producer sends the event, until the time that the consumer(s) receive the consequences of this event), and can relate to a specific function (agent) in the event processing network, so when latency is mentioned - it should be defined - what is really being measured. The deadline typically refers to time constraint of the latency.
The term throughput designates the amount of events that the system can get as an input in a given time interval (1 second, 1 minute etc...), throughput does not necessarily entails that all these events are handled within this time interval - it may be the case that the events are put into a buffer, and all of them are handled within the next 6 hours - so in this case, the throughput is mainly determine by the capacity of input channels and buffers and not in the speed of processing. Of course, there are applications that require high throughput together with individual hard real-time constraint on each event.
The "Right-time" to react is determined by these time constraints, and determine the scheduling and optimization requirements - more later.