Aperiodic And Sporadic Tasks

Aperiodic and Sporadic Tasks
Earlier, we pointed out that a real-time system is invariably required to respond to external events, and to respond, it executes aperiodic or sporadic jobs whose release times are not known a priori. An operator’s adjustment of the sensitivity setting of a radar surveillance system is an example. The radar system must continue to operate, but in addition, it also must respond to the operator’s command. Similarly, when a pilot changes the autopilot from cruise mode to standby mode, the system must respond by reconfiguring itself, while continuing to execute the control tasks that fly the airplane. A command and control system must process sporadic data messages, in addition to the continuous voice and video traffic.

In the periodic task model, the workload generated in response to these unexpected events is captured by aperiodic and sporadic tasks. Each aperiodic or sporadic task is a stream of aperiodic or sporadic jobs, respectively. The interarrival times between consecutive jobs in such a task may vary widely and, in particular, can be arbitrarily small. The jobs in each task model the work done by the system in response to events of the same type. For example, the jobs that execute to change the detection threshold of the radar system are in one task; the jobs that change the operation mode of the autopilot are in one task; and the jobs that process sporadic data messages are in one task, and so on.

Specifically, the jobs in each aperiodic task are similar in the sense that they have the same statistical behavior and the same timing requirement. Their interarrival times are identically distributed random variables with some probability distribution A(x). Similarly, the execution times of jobs in each aperiodic (or sporadic) task are identically distributed random variables, each distributed according to the probability distribution B(x). These assumptions mean that the statistical behavior of the system and its environment do not change with time,that is, the system is stationary. That the system is stationary is usually valid in time intervals of length on the order of H, in particular, within any hyperperiod of the periodic tasks during which no periodic tasks are added or deleted.

We say that a task is aperiodic if the jobs in it have either soft deadlines or no deadlines. The task to adjust radar’s sensitivity is an example. We want the system to be responsive, that is, to complete each adjustment as soon as possible. On the other hand, a late response is annoying but tolerable. We therefore want to optimize the responsiveness of the system for the aperiodic jobs, but never at the expense of hard real-time tasks whose deadlines must be met at all times.

In contrast, an autopilot system is required to respond to a pilot’s command to disengage the autopilot and take over the control manually within a specific time. Similarly, when a transient fault occurs, a fault-tolerant system may be required to detect the fault and recover from it in time. The jobs that execute in response to these events have hard deadlines. Tasks containing jobs that are released at random time instants and have hard deadlines are sporadic tasks. We treat them as hard real-time tasks. Our primary concern is to ensure that their deadlines are always met; minimizing their response times is of secondary importance.