Require Import rt.restructuring.model.processor.ideal. Require Import rt.restructuring.model.readiness.basic. Require Import rt.restructuring.analysis.edf.rta.nonpr_reg.response_time_bound. Require Export rt.restructuring.analysis.basic_facts.preemption.task.preemptive. Require Export rt.restructuring.analysis.basic_facts.preemption.rtc_threshold.preemptive. (** Assume we have a fully preemptive model. *) Require Import rt.restructuring.model.task.preemption.fully_preemptive. From mathcomp Require Import ssreflect ssrbool eqtype ssrnat seq path fintype bigop. (** * RTA for Fully Preemptive EDF Model *) (** In this section we prove the RTA theorem for the fully preemptive EDF model *) Section RTAforFullyPreemptiveEDFModelwithArrivalCurves. (** 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. (** 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 of the arrival sequence ... *) Variable sched : schedule (ideal.processor_state Job). Hypothesis H_jobs_come_from_arrival_sequence: jobs_come_from_arrival_sequence sched arr_seq. (** ... 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. (** 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 := (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 = 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 of fully preemptive scheduling. *) Theorem uniprocessor_response_time_bound_fully_preemptive_edf: response_time_bounded_by tsk R. Proof. have BLOCK: blocking_bound ts tsk = 0. { by rewrite /blocking_bound /parameters.task_max_nonpreemptive_segment /fully_preemptive.fully_preemptive_model subnn big1_eq. } eapply uniprocessor_response_time_bound_edf_with_bounded_nonpreemptive_segments with (L0 := L) . all: eauto 2 with basic_facts. - move => A /andP [LT NEQ]. specialize (H_R_is_maximum A); feed H_R_is_maximum. { by apply/andP; split. } move: H_R_is_maximum => [F [FIX BOUND]]. exists F; split. + by rewrite BLOCK add0n subnn subn0. + by rewrite subnn addn0. Qed. End RTAforFullyPreemptiveEDFModelwithArrivalCurves.