Library prosa.model.task.arrival.curve_as_rbf
Require Export prosa.util.all.
Require Export prosa.model.task.arrival.request_bound_functions.
Require Export prosa.model.task.arrival.curves.
Require Export prosa.model.task.arrival.request_bound_functions.
Require Export prosa.model.task.arrival.curves.
Converting an Arrival Curve + Worst-Case/Best-Case to a Request-Bound Function (RBF)
Consider any type of tasks with a given cost ...
... and any type of jobs associated with these tasks.
Let MaxArr and MinArr represent two arrivals curves. MaxArr upper-bounds
the possible number or arrivals for a given task, whereas MinArr lower-bounds it.
We define the conversion to a request-bound function as the product of the task cost and the
number of arrivals during Δ. In the upper-bounding case, the cost of a task will represent
the WCET of its jobs. Symmetrically, in the lower-bounding case, the cost of a task will
represent the BCET of its jobs.
Definition task_max_rbf (arrivals : Task → duration → nat) task Δ := task_cost task × arrivals task Δ.
Definition task_min_rbf (arrivals : Task → duration → nat) task Δ := task_min_cost task × arrivals task Δ.
Definition task_min_rbf (arrivals : Task → duration → nat) task Δ := task_min_cost task × arrivals task Δ.
Finally, we show that the newly defined functions are indeed request-bound functions.
In the following section, we prove that the transformation yields a request-bound
function that conserves correctness properties in both the upper-bounding
and lower-bounding cases.
First, we establish the validity of the transformation for a single, given task.
Consider an arbitrary task tsk ...
... and any job arrival sequence.
First, note that any valid upper-bounding arrival curve, after being
converted, is a valid request-bound function.
Theorem valid_arrival_curve_to_max_rbf:
∀ (arrivals : Task → duration → nat),
valid_arrival_curve (arrivals tsk) →
valid_request_bound_function ((task_max_rbf arrivals) tsk).
∀ (arrivals : Task → duration → nat),
valid_arrival_curve (arrivals tsk) →
valid_request_bound_function ((task_max_rbf arrivals) tsk).
The same idea can be applied in the lower-bounding case.
Theorem valid_arrival_curve_to_min_rbf:
∀ (arrivals : Task → duration → nat),
valid_arrival_curve (arrivals tsk) →
valid_request_bound_function ((task_min_rbf arrivals) tsk).
∀ (arrivals : Task → duration → nat),
valid_arrival_curve (arrivals tsk) →
valid_request_bound_function ((task_min_rbf arrivals) tsk).
Next, we prove that the task respects the request-bound function in
the upper-bounding case. Note that, for this to work, we assume that the
cost of tasks upper-bounds the cost of the jobs belonging to them (i.e.,
the task cost is the worst-case).
Theorem respects_arrival_curve_to_max_rbf:
jobs_have_valid_job_costs →
respects_max_arrivals arr_seq tsk (MaxArr tsk) →
respects_max_request_bound arr_seq tsk ((task_max_rbf MaxArr) tsk).
jobs_have_valid_job_costs →
respects_max_arrivals arr_seq tsk (MaxArr tsk) →
respects_max_request_bound arr_seq tsk ((task_max_rbf MaxArr) tsk).
Finally, we prove that the task respects the request-bound function also in
the lower-bounding case. This time, we assume that the cost of tasks lower-bounds
the cost of the jobs belonging to them. (i.e., the task cost is the best-case).
Theorem respects_arrival_curve_to_min_rbf:
jobs_have_valid_min_job_costs →
respects_min_arrivals arr_seq tsk (MinArr tsk) →
respects_min_request_bound arr_seq tsk ((task_min_rbf MinArr) tsk).
End SingleTask.
jobs_have_valid_min_job_costs →
respects_min_arrivals arr_seq tsk (MinArr tsk) →
respects_min_request_bound arr_seq tsk ((task_min_rbf MinArr) tsk).
End SingleTask.
Next, we lift the results to the previous section to an arbitrary task set.
Let ts be an arbitrary task set...
... and consider any job arrival sequence.
First, we generalize the validity of the transformation to a task set both in
the upper-bounding case ...
Corollary valid_taskset_arrival_curve_to_max_rbf:
valid_taskset_arrival_curve ts MaxArr →
valid_taskset_request_bound_function ts MaxArrivalsRBF.
valid_taskset_arrival_curve ts MaxArr →
valid_taskset_request_bound_function ts MaxArrivalsRBF.
... and in the lower-bounding case.
Corollary valid_taskset_arrival_curve_to_min_rbf:
valid_taskset_arrival_curve ts MinArr →
valid_taskset_request_bound_function ts MinArrivalsRBF.
valid_taskset_arrival_curve ts MinArr →
valid_taskset_request_bound_function ts MinArrivalsRBF.
Second, we show that a task set that respects a given arrival curve also respects
the produced request-bound function, lifting the result obtained in the single-task
case. The result is valid in the upper-bounding case...
Corollary taskset_respects_arrival_curve_to_max_rbf:
jobs_have_valid_job_costs →
taskset_respects_max_arrivals arr_seq ts →
taskset_respects_max_request_bound arr_seq ts.
jobs_have_valid_job_costs →
taskset_respects_max_arrivals arr_seq ts →
taskset_respects_max_request_bound arr_seq ts.
...as well as in the lower-bounding case.
Corollary taskset_respects_arrival_curve_to_min_rbf:
jobs_have_valid_min_job_costs →
taskset_respects_min_arrivals arr_seq ts →
taskset_respects_min_request_bound arr_seq ts.
End TaskSet.
End Facts.
End ArrivalCurveToRBF.
jobs_have_valid_min_job_costs →
taskset_respects_min_arrivals arr_seq ts →
taskset_respects_min_request_bound arr_seq ts.
End TaskSet.
End Facts.
End ArrivalCurveToRBF.
We add the lemmas into the "Hint Database" basic_rt_facts so that
they become available for proof automation.
Global Hint Resolve
valid_arrival_curve_to_max_rbf
respects_arrival_curve_to_max_rbf
valid_taskset_arrival_curve_to_max_rbf
taskset_respects_arrival_curve_to_max_rbf
: basic_rt_facts.
valid_arrival_curve_to_max_rbf
respects_arrival_curve_to_max_rbf
valid_taskset_arrival_curve_to_max_rbf
taskset_respects_arrival_curve_to_max_rbf
: basic_rt_facts.