Require Import rt.util.all.
Require Import rt.restructuring.behavior.all.
Require Import rt.restructuring.analysis.basic_facts.all.
Require Import rt.restructuring.analysis.definitions.job_properties.
Require Import rt.restructuring.model.task.
Require Import rt.restructuring.model.aggregate.workload.
Require Import rt.restructuring.model.processor.ideal.
Require Import rt.restructuring.model.readiness.basic.
Require Import rt.restructuring.model.arrival.arrival_curves.
Require Import rt.restructuring.model.preemption.floating.
Require Import rt.restructuring.model.schedule.work_conserving.
Require Import rt.restructuring.model.priority.classes.
Require Import rt.restructuring.analysis.facts.edf.
Require Import rt.restructuring.model.schedule.priority_driven.
Require Import rt.restructuring.analysis.arrival.workload_bound.
Require Import rt.restructuring.analysis.arrival.rbf.
Require Import rt.restructuring.analysis.edf.rta.nonpr_reg.response_time_bound.
Require Export rt.restructuring.analysis.basic_facts.preemption.job.limited.
Require Export rt.restructuring.analysis.basic_facts.preemption.task.floating.
Require Export rt.restructuring.analysis.basic_facts.preemption.rtc_threshold.floating.
Require Export rt.restructuring.analysis.facts.priority_inversion_is_bounded.
From mathcomp Require Import ssreflect ssrbool eqtype ssrnat seq path fintype bigop.
(** * RTA for Model with Floating Non-Preemptive Regions *)
(** In this module we prove the RTA theorem for floating non-preemptive regions EDF model. *)
Section RTAforModelWithFloatingNonpreemptiveRegionsWithArrivalCurves.
(** Consider any type of tasks ... *)
Context {Task : TaskType}.
Context `{TaskCost Task}.
Context `{TaskDeadline Task}.
(** ... and any type of jobs associated with these tasks. *)
Context {Job : JobType}.
Context `{JobTask Job Task}.
Context `{JobArrival Job}.
Context `{JobCost Job}.
(** For clarity, let's denote the relative deadline of a task as D. *)
Let D tsk := task_deadline tsk.
(** Consider the EDF policy that indicates a higher-or-equal priority relation. *)
Let EDF := EDF Job.
(** Consider any arrival sequence with consistent, non-duplicate arrivals. *)
Variable arr_seq : arrival_sequence Job.
Hypothesis H_arrival_times_are_consistent : consistent_arrival_times arr_seq.
Hypothesis H_arr_seq_is_a_set : arrival_sequence_uniq arr_seq.
(** Assume we have the model with floating nonpreemptive regions.
I.e., for each task only the length of the maximal nonpreemptive
segment is known _and_ each job level is divided into a number
of nonpreemptive segments by inserting preemption points. *)
Context `{JobPreemptionPoints Job}
`{TaskMaxNonpreemptiveSegment Task}.
Hypothesis H_valid_task_model_with_floating_nonpreemptive_regions:
valid_model_with_floating_nonpreemptive_regions arr_seq.
(** Consider an arbitrary task set ts, ... *)
Variable ts : list Task.
(** ... assume that all jobs come from this task set, ... *)
Hypothesis H_all_jobs_from_taskset : all_jobs_from_taskset arr_seq ts.
(** ... and the cost of a job cannot be larger than the task cost. *)
Hypothesis H_job_cost_le_task_cost:
cost_of_jobs_from_arrival_sequence_le_task_cost arr_seq.
(** Let max_arrivals be a family of valid arrival curves, i.e., for
any task tsk in ts [max_arrival tsk] is (1) an arrival bound of
tsk, and (2) it is a monotonic function that equals 0 for the
empty interval delta = 0. *)
Context `{MaxArrivals Task}.
Hypothesis H_valid_arrival_curve : valid_taskset_arrival_curve ts max_arrivals.
Hypothesis H_is_arrival_curve : taskset_respects_max_arrivals arr_seq ts.
(** Let tsk be any task in ts that is to be analyzed. *)
Variable tsk : Task.
Hypothesis H_tsk_in_ts : tsk \in ts.
(** Next, consider any ideal uniprocessor schedule with limited
preemptions of this arrival sequence ... *)
Variable sched : schedule (ideal.processor_state Job).
Hypothesis H_jobs_come_from_arrival_sequence:
jobs_come_from_arrival_sequence sched arr_seq.
Hypothesis H_schedule_with_limited_preemptions:
valid_schedule_with_limited_preemptions arr_seq sched.
(** ... where jobs do not execute before their arrival or after completion. *)
Hypothesis H_jobs_must_arrive_to_execute : jobs_must_arrive_to_execute sched.
Hypothesis H_completed_jobs_dont_execute : completed_jobs_dont_execute sched.
(** Assume we have sequential tasks, i.e, jobs from the
same task execute in the order of their arrival. *)
Hypothesis H_sequential_tasks : sequential_tasks sched.
(** Next, we assume that the schedule is a work-conserving schedule... *)
Hypothesis H_work_conserving : work_conserving arr_seq sched.
(** ... and the schedule respects the policy defined by the
job_preemptable function (i.e., jobs have bounded nonpreemptive
segments). *)
Hypothesis H_respects_policy : respects_policy_at_preemption_point arr_seq sched.
(** Let's define some local names for clarity. *)
Let response_time_bounded_by :=
task_response_time_bound arr_seq sched.
Let task_rbf_changes_at A := task_rbf_changes_at tsk A.
Let bound_on_total_hep_workload_changes_at :=
bound_on_total_hep_workload_changes_at ts tsk.
(** We introduce the abbreviation "rbf" for the task request bound function,
which is defined as [task_cost(T) × max_arrivals(T,Δ)] for a task T. *)
Let rbf := task_request_bound_function.
(** Next, we introduce task_rbf as an abbreviation
for the task request bound function of task tsk. *)
Let task_rbf := rbf tsk.
(** Using the sum of individual request bound functions, we define the request bound
function of all tasks (total request bound function). *)
Let total_rbf := total_request_bound_function ts.
(** We define a bound for the priority inversion caused by jobs with lower priority. *)
Definition blocking_bound :=
\max_(tsk_other <- ts | (tsk_other != tsk) && (D tsk_other > D tsk))
(task_max_nonpreemptive_segment tsk_other - ε).
(** Next, we define an upper bound on interfering workload received from jobs
of other tasks with higher-than-or-equal priority. *)
Let bound_on_total_hep_workload A Δ :=
\sum_(tsk_o <- ts | tsk_o != tsk)
rbf tsk_o (minn ((A + ε) + D tsk - D tsk_o) Δ).
(** Let L be any positive fixed point of the busy interval recurrence. *)
Variable L : duration.
Hypothesis H_L_positive : L > 0.
Hypothesis H_fixed_point : L = total_rbf L.
(** To reduce the time complexity of the analysis, recall the notion of search space. *)
Let is_in_search_space (A : duration) :=
(A < L) && (task_rbf_changes_at A || bound_on_total_hep_workload_changes_at A).
(** Consider any value R, and assume that for any given arrival offset A in the search space,
there is a solution of the response-time bound recurrence which is bounded by R. *)
Variable R : duration.
Hypothesis H_R_is_maximum:
forall (A : duration),
is_in_search_space A ->
exists (F : duration),
A + F = blocking_bound + task_rbf (A + ε) + bound_on_total_hep_workload A (A + F) /\
F <= R.
(** Now, we can leverage the results for the abstract model with
bounded nonpreemptive segments to establish a response-time
bound for the more concrete model with floating nonpreemptive
regions. *)
Theorem uniprocessor_response_time_bound_edf_with_floating_nonpreemptive_regions:
response_time_bounded_by tsk R.
Proof.
move: (H_valid_task_model_with_floating_nonpreemptive_regions) => [LIMJ JMLETM].
move: (LIMJ) => [BEG [END _]].
eapply uniprocessor_response_time_bound_edf_with_bounded_nonpreemptive_segments with (L0 := L).
all: eauto 2 with basic_facts.
{ rewrite subnn.
intros A SP.
apply H_R_is_maximum in SP.
move: SP => [F [EQ LE]].
exists F.
by rewrite subn0 addn0; split.
}
Qed.
End RTAforModelWithFloatingNonpreemptiveRegionsWithArrivalCurves.