Library prosa.classic.analysis.uni.susp.dynamic.jitter.rta_by_reduction
Require Import prosa.classic.util.all.
Require Import prosa.classic.model.priority prosa.classic.model.suspension.
Require Import prosa.classic.model.arrival.basic.job prosa.classic.model.arrival.basic.task
prosa.classic.model.arrival.basic.arrival_sequence prosa.classic.model.arrival.basic.task_arrival.
Require Import prosa.classic.model.arrival.jitter.job.
Require Import prosa.classic.model.schedule.uni.schedulability prosa.classic.model.schedule.uni.service
prosa.classic.model.schedule.uni.workload
prosa.classic.model.schedule.uni.response_time.
Require Import prosa.classic.model.schedule.uni.jitter.schedule
prosa.classic.model.schedule.uni.jitter.platform.
Require Import prosa.classic.model.schedule.uni.susp.suspension_intervals
prosa.classic.model.schedule.uni.susp.schedule
prosa.classic.model.schedule.uni.susp.valid_schedule
prosa.classic.model.schedule.uni.susp.platform.
Require Import prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_schedule
prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_schedule_properties
prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_schedule_service
prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_taskset_generation.
From mathcomp Require Import ssreflect ssrbool ssrfun eqtype ssrnat seq fintype bigop.
(* In this file, we determine task response-time bounds in suspension-aware
schedules using a reduction to jitter-aware schedules. *)
Module RTAByReduction.
Import TaskArrival SporadicTaskset Suspension Priority Workload Service Schedulability
UniprocessorScheduleWithJitter ResponseTime SuspensionIntervals ValidSuspensionAwareSchedule.
Module susp_aware := PlatformWithSuspensions.
Module reduction := JitterScheduleConstruction.
Module reduction_prop := JitterScheduleProperties.
Module reduction_serv := JitterScheduleService.
Module ts_gen := JitterTaskSetGeneration.
Section ComparingResponseTimeBounds.
Context {Task: eqType}.
Variable task_period: Task → time.
Variable task_deadline: Task → time.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_deadline: Job → time.
Variable job_task: Job → Task.
Require Import prosa.classic.model.priority prosa.classic.model.suspension.
Require Import prosa.classic.model.arrival.basic.job prosa.classic.model.arrival.basic.task
prosa.classic.model.arrival.basic.arrival_sequence prosa.classic.model.arrival.basic.task_arrival.
Require Import prosa.classic.model.arrival.jitter.job.
Require Import prosa.classic.model.schedule.uni.schedulability prosa.classic.model.schedule.uni.service
prosa.classic.model.schedule.uni.workload
prosa.classic.model.schedule.uni.response_time.
Require Import prosa.classic.model.schedule.uni.jitter.schedule
prosa.classic.model.schedule.uni.jitter.platform.
Require Import prosa.classic.model.schedule.uni.susp.suspension_intervals
prosa.classic.model.schedule.uni.susp.schedule
prosa.classic.model.schedule.uni.susp.valid_schedule
prosa.classic.model.schedule.uni.susp.platform.
Require Import prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_schedule
prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_schedule_properties
prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_schedule_service
prosa.classic.analysis.uni.susp.dynamic.jitter.jitter_taskset_generation.
From mathcomp Require Import ssreflect ssrbool ssrfun eqtype ssrnat seq fintype bigop.
(* In this file, we determine task response-time bounds in suspension-aware
schedules using a reduction to jitter-aware schedules. *)
Module RTAByReduction.
Import TaskArrival SporadicTaskset Suspension Priority Workload Service Schedulability
UniprocessorScheduleWithJitter ResponseTime SuspensionIntervals ValidSuspensionAwareSchedule.
Module susp_aware := PlatformWithSuspensions.
Module reduction := JitterScheduleConstruction.
Module reduction_prop := JitterScheduleProperties.
Module reduction_serv := JitterScheduleService.
Module ts_gen := JitterTaskSetGeneration.
Section ComparingResponseTimeBounds.
Context {Task: eqType}.
Variable task_period: Task → time.
Variable task_deadline: Task → time.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_deadline: Job → time.
Variable job_task: Job → Task.
Basic Setup & Setting
(* Let ts be any task set with constrained deadlines. *)
Variable ts: seq Task.
Hypothesis H_constrained_deadlines:
constrained_deadline_model task_period task_deadline ts.
(* Consider any consistent, duplicate-free job arrival sequence... *)
Variable arr_seq: arrival_sequence Job.
Hypothesis H_arrival_times_are_consistent:
arrival_times_are_consistent job_arrival arr_seq.
Hypothesis H_arrival_sequence_is_a_set: arrival_sequence_is_a_set arr_seq.
(* ...with sporadic arrivals... *)
Hypothesis H_sporadic_arrivals:
sporadic_task_model task_period job_arrival job_task arr_seq.
(* ...and in which all jobs come from task set ts. *)
Hypothesis H_jobs_from_taskset:
∀ j, arrives_in arr_seq j → job_task j \in ts.
(* Since we consider real-time tasks, assume that job deadlines are equal to task deadlines. *)
Hypothesis H_job_deadlines_equal_task_deadlines:
∀ j, arrives_in arr_seq j → job_deadline j = task_deadline (job_task j).
(* Consider any FP policy that is reflexive, transitive and total.
Note that the policy does not depend on the schedule. *)
Variable higher_eq_priority: FP_policy Task.
Hypothesis H_priority_is_reflexive: FP_is_reflexive higher_eq_priority.
Hypothesis H_priority_is_transitive: FP_is_transitive higher_eq_priority.
Hypothesis H_priority_is_total: FP_is_total_over_task_set higher_eq_priority ts.
Let job_higher_eq_priority := FP_to_JLDP job_task higher_eq_priority.
(* Assume that jobs and tasks have associated costs... *)
Variable job_cost: Job → time.
Variable task_cost: Task → time.
(* ...and suspension times. *)
Variable job_suspension_duration: job_suspension Job.
Variable task_suspension_bound: Task → time.
(* Assume that jobs have positive cost. *)
Hypothesis H_positive_costs:
∀ j, arrives_in arr_seq j → job_cost j > 0.
(* Next, consider any valid suspension-aware schedule of this arrival sequence.
(Note: see prosa.classic.model.schedule.uni.susp.valid_schedule.v for details) *)
Variable sched_susp: schedule Job.
Hypothesis H_valid_schedule:
valid_suspension_aware_schedule job_arrival arr_seq job_higher_eq_priority
job_suspension_duration job_cost sched_susp.
Analysis Setup
(* Now we proceed with the proof. Let tsk be the task to be analyzed. *)
Variable tsk: Task.
Hypothesis H_tsk_in_ts: tsk \in ts.
(* For simplicity, let's define some local names. *)
Let other_hep_task tsk_other :=
higher_eq_priority tsk_other tsk && (tsk_other != tsk).
Let task_response_time_in_sched_susp_bounded_by :=
is_response_time_bound_of_task job_arrival job_cost job_task arr_seq sched_susp.
Let job_response_time_in_sched_susp_bounded_by :=
is_response_time_bound_of_job job_arrival job_cost sched_susp.
Let completed_in_sched_susp_by := completed_by job_cost sched_susp.
Let job_misses_no_deadline_in_sched_susp :=
job_misses_no_deadline job_arrival job_cost job_deadline sched_susp.
(* Assume that each task is associated a value R... *)
Variable R: Task → time.
(* ...that bounds the response-time of all tasks with higher-or-equal priority
(other than tsk) in the suspension-aware schedule sched_susp. *)
Hypothesis H_valid_response_time_bound_of_hp_tasks:
∀ tsk_hp,
tsk_hp \in ts →
other_hep_task tsk_hp →
task_response_time_in_sched_susp_bounded_by tsk_hp (R tsk_hp).
(* The existence of those response-time bounds implies that we can compute the actual
response times of the higher-priority jobs in sched_susp. *)
Definition actual_response_time (j_hp: Job) : time :=
[pick-min r ≤ R (job_task j_hp) |
job_response_time_in_sched_susp_bounded_by j_hp r].
(* Next, let j be any job of tsk... *)
Variable j: Job.
Hypothesis H_j_arrives: arrives_in arr_seq j.
Hypothesis H_job_of_tsk: job_task j = tsk.
(* ...and assume that all the previous jobs of same task do not miss any
deadlines in sched_susp. *)
Hypothesis H_no_deadline_misses_for_previous_jobs:
∀ j0,
arrives_in arr_seq j0 →
job_arrival j0 < job_arrival j →
job_task j0 = job_task j →
job_misses_no_deadline_in_sched_susp j0.
Instantiation of the Reduction
(* First, recall the parameters of the jitter-aware task set. *)
Let inflated_task_cost := ts_gen.inflated_task_cost task_cost task_suspension_bound tsk.
Let task_jitter := ts_gen.task_jitter task_cost higher_eq_priority tsk.
(* Then, using the actual response times of higher-priority jobs as parameters, we construct
the jitter-aware schedule from sched_susp. *)
Let sched_jitter := reduction.sched_jitter job_arrival job_task arr_seq higher_eq_priority
job_cost job_suspension_duration j actual_response_time.
(* Next, recall the corresponding job parameters... *)
Let inflated_job_cost := reduction.inflated_job_cost job_cost job_suspension_duration j.
Let job_jitter := reduction.job_jitter job_arrival job_task higher_eq_priority job_cost j
actual_response_time.
(* ...and the definition of job response-time bound in sched_jitter. *)
Let job_response_time_in_sched_jitter_bounded_by :=
is_response_time_bound_of_job job_arrival inflated_job_cost sched_jitter.
Central Hypothesis
(* Assume that using some jitter-aware RTA, we determine that
(R tsk) is a response-time bound for tsk in sched_jitter. *)
Hypothesis H_valid_response_time_bound_in_sched_jitter:
job_response_time_in_sched_jitter_bounded_by j (R tsk).
(* Then, we use the properties of the reduction to prove that (R tsk) is also a
response-time bound for tsk in the original schedule sched_susp. *)
Theorem valid_response_time_bound_in_sched_susp:
job_response_time_in_sched_susp_bounded_by j (R tsk).
End ComparingResponseTimeBounds.
End RTAByReduction.