Library prosa.analysis.facts.priority.jlfp_with_fp

Require Import prosa.model.priority.elf.
Require Export prosa.analysis.facts.priority.classes.
Require Export prosa.analysis.definitions.priority.classes.
Require Export prosa.analysis.facts.model.workload.

In this file, we prove lemmas that are useful when both an FP policy and a JLFP policy are present in context.
In this section, we prove a lemma about workload partitioning which is useful for reasoning about the interference bound function for the ELF scheduling policy.
Section WorkloadTaskSum.

Consider any type of tasks with relative priority points...
  Context {Task : TaskType} `{PriorityPoint Task}.

...and jobs of these tasks.
  Context {Job : JobType} `{JobArrival Job} `{JobTask Job Task} `{JobCost Job} .

Let us consider an FP policy and a compatible JLFP policy present in context.
  Context {FP : FP_policy Task}.
  Context {JLFP : JLFP_policy Job}.
  Hypothesis JLFP_FP_is_compatible : JLFP_FP_compatible JLFP FP.

Consider any valid arrival sequence arr_seq.
  Variable arr_seq : arrival_sequence Job.
  Hypothesis H_valid_arrival_sequence : valid_arrival_sequence (arr_seq).

We consider an arbitrary task set ts...
  Variable ts : seq Task.
  Hypothesis H_task_set : uniq ts.

... and assume that all jobs stem from tasks in this task set.
  Hypothesis H_all_jobs_from_taskset : all_jobs_from_taskset 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.

We define a predicate to identify others tasks which have equal priority as tsk.
  Definition other_ep_task := fun tsk_o ⇒ (ep_task tsk tsk_o) && (tsk_o != tsk).

We consider a job j belonging to this task ...
  Variable j : Job.
  Hypothesis H_job_of_task : job_of_task tsk j.

... and focus on the jobs arriving in an arbitrary interval [t1, t2).
  Variable t1 t2 : duration.
  Let jobs_arrived := arrivals_between arr_seq t1 t2.

We first consider jobs that belong to other tasks that have equal priority as tsk and have higher-or-equal priority JLFP than j.
  Definition hep_job_of_ep_other_task :=
    fun j' : Job ⇒
      hep_job j' j
      && ep_task (job_task j') (job_task j)
      && (job_task j' != job_task j).

We then establish that the cumulative workload of these jobs can be partitioned task-wise.
  Lemma hep_workload_from_other_ep_partitioned_by_tasks :
    workload_of_jobs hep_job_of_ep_other_task jobs_arrived
      = \sum_(tsk_o <- ts | other_ep_task tsk_o)
        workload_of_jobs
          (fun j0 ⇒ hep_job_of_ep_other_task j0 && (job_task j0 == tsk_o))
          jobs_arrived.

Now we focus on jobs belonging to tasks which have higher priority than tsk.
  Definition from_hp_task (j' : Job) :=
    hp_task (job_task j') (job_task j).

We also identify higher-or-equal-priority jobs JLFP that belong to (1) tasks having higher priority than tsk ...
  Definition hep_from_hp_task (j' : Job) :=
    hep_job j' j && hp_task (job_task j') (job_task j).

... (2) tasks having equal priority as tsk.
  Definition hep_from_ep_task (j' : Job) :=
    hep_job j' j && ep_task (job_task j') (job_task j).

First, we establish that the cumulative workload of higher-or-equal-priority jobs belonging to tasks having higher priority than tsk is equal to the cumulative workload of jobs belonging to higher-priority tasks.
  Lemma hep_hp_workload_hp :
    workload_of_jobs hep_from_hp_task jobs_arrived = workload_of_jobs from_hp_task jobs_arrived.

We then establish that the cumulative workload of higher-or-equal priority jobs is equal to the sum of cumulative workload of higher-or-equal priority jobs belonging to higher-priority tasks and the cumulative workload of higher-or-equal-priority jobs belonging to equal-priority tasks.
  Lemma hep_workload_partitioning_taskwise :
    workload_of_higher_or_equal_priority_jobs j jobs_arrived
    = workload_of_jobs hep_from_hp_task jobs_arrived
      + workload_of_jobs hep_from_ep_task jobs_arrived.

End WorkloadTaskSum.