RTA for FP Scheduling with Floating Non-Preemptive Regions on Uniprocessors under the Average Resource Model

In the following, we derive a response-time analysis for FP schedulers, assuming a workload of sporadic real-time tasks with floating non-preemptive regions, characterized by arbitrary arrival curves, executing upon a uniprocessor under the average resource model (inspired by the paper "Periodic Resource Model for Compositional Real-Time Guarantees" by Shin & Lee, RTSS 2003). To this end, we instantiate the sequential variant of abstract Restricted-Supply Analysis (aRSA) as provided in the prosa.analysis.abstract.restricted_supply module.

Defining the System Model

Before any formal claims can be stated, an initial setup is needed to define the system model under consideration. To this end, we next introduce and define the following notions using Prosa's standard definitions and behavioral semantics:

• tasks, jobs, and their parameters,
• the task set and the task under analysis,
• the processor model,
• the sequence of job arrivals,
• the absence of self-suspensions,
• an arbitrary schedule of the task set, and finally,
• the resource-supply model.

Tasks and Jobs

Consider tasks characterized by a WCET task_cost, an arrival curve max_arrivals, and a bound on the task's longest non-preemptive segment task_max_nonpreemptive_segment, ...

... and their associated jobs, where each job has a corresponding task job_task, an execution time job_cost, an arrival time job_arrival, and a list of preemption points job_preemptive_points.

We assume that jobs are limited-preemptive.

The Task Set and the Task Under Analysis

Consider an arbitrary task set ts, and ...

... let tsk be any task in ts that is to be analyzed.

Processor Model

Consider any kind of fully-supply-consuming, unit-supply processor state model.

The Job Arrival Sequence

Allow for any possible arrival sequence arr_seq consistent with the parameters of the task set ts. That is, arr_seq is a valid arrival sequence in which each job's cost is upper-bounded by its task's WCET, every job stems from a task in ts, and the number of arrivals respects each task's max_arrivals bound.

Assume a model with floating non-preemptive regions. I.e., for each task only the length of the maximal non-preemptive segment is known and each job is divided into a number of non-preemptive segments by inserting preemption points.

Absence of Self-Suspensions

We assume the classic (i.e., Liu & Layland) model of readiness without jitter or self-suspensions, wherein pending jobs are always ready.

The Schedule

Consider an arbitrary fixed-priority policy FP that indicates a higher-or-equal priority relation among the tasks in ts, and assume that the relation is reflexive and transitive.

Consider a work-conserving, valid uniprocessor schedule with limited preemptions that corresponds to the given arrival sequence arr_seq (and hence the given task set ts).

We assume that the schedule respects the given FP scheduling policy.

Furthermore, we require that the schedule ensures that jobs of the same task are executed in the order of their arrival.

Average Resource Model

Assume that the processor supply follows the *average resource model*. Under this model, for any interval [t1, t2), and given a resource period Π, a resource allocation time Θ, and a supply delay ν, the processor provides at least (t2 - t1 - ν) ⋅ Θ / Π units of supply. Intuitively, this means that on _average, the processor delivers Θ units of output every Π units of time, while the distribution of supply is not ideal and is subject to fluctuations bounded by ν. Furthermore, let arm_sbf Π Θ ν denote the SBF, which, as proven in prosa.analysis.facts.model.sbf.average, is a valid SBF.

Maximum Length of a Busy Interval

In order to apply aRSA, we require a bound on the maximum busy-window length. To this end, let L be any positive solution of the busy-interval "recurrence" (i.e., inequality) arm_sbf Π Θ ν L ≥ blocking_bound ts tsk + total_hep_request_bound_function_FP ts tsk L, as defined below. As the lemma busy_intervals_are_bounded_rs_fp shows, under FP scheduling, this condition is sufficient to guarantee that the maximum busy-window length is at most L, i.e., the length of any busy interval is bounded by L.

Response-Time Bound

Having established all necessary preliminaries, it is finally time to state the claimed response-time bound R. A value R is a response-time bound for task tsk if, for any given offset A in the search space (w.r.t. the busy-window bound L), the response-time bound "recurrence" (i.e., inequality) has a solution F not exceeding A + R.

Finally, using the sequential variant of abstract restricted-supply analysis, we establish that, given a bound on the maximum busy-window length L, any such R is indeed a sound response-time bound for task tsk under FP scheduling with floating non-preemptive regions on a unit-speed uniprocessor under the average resource model.