Library prosa.analysis.facts.behavior.arrivals

Require Export prosa.behavior.all.
Require Export prosa.util.all.
Require Export prosa.model.task.arrivals.

Arrival Sequence

First, we relate the stronger to the weaker arrival predicates.

Section ArrivalPredicates.

Consider any kinds of jobs with arrival times.

Context {Job : JobType} `{JobArrival Job}.

A job that arrives in some interval [t1, t2) certainly arrives before time t2.

  Lemma arrived_between_before:
    ∀ j t1 t2,
      arrived_between j t1 t2 →
      arrived_before j t2.

A job that arrives before a time t certainly has arrived by time t.

  Lemma arrived_before_has_arrived:
    ∀ j t,
      arrived_before j t →
      has_arrived j t.

Furthermore, we restate a common hypothesis to make its implication easier to discover.

  Lemma consistent_times_valid_arrival :
    ∀ arr_seq,
      valid_arrival_sequence arr_seq → consistent_arrival_times arr_seq.

We restate another common hypothesis to make its implication easier to discover.

  Lemma uniq_valid_arrival :
    ∀ arr_seq,
      valid_arrival_sequence arr_seq → arrival_sequence_uniq arr_seq.

End ArrivalPredicates.

In this section, we relate job readiness to has_arrived.

Section Arrived.

Consider any kinds of jobs and any kind of processor state.

Context {Job : JobType} {PState : ProcessorState Job}.

Consider any schedule...

Variable sched : schedule PState.

...and suppose that jobs have a cost, an arrival time, and a notion of readiness.

  Context `{JobCost Job}.
  Context `{JobArrival Job}.
  Context {jr : JobReady Job PState}.

First, we note that readiness models are by definition consistent w.r.t. pending.

  Lemma any_ready_job_is_pending:
    ∀ j t,
      job_ready sched j t → pending sched j t.

Next, we observe that a given job must have arrived to be ready...

Lemma ready_implies_arrived :
∀ j t, job_ready sched j t → has_arrived j t.

...and lift this observation also to the level of whole schedules.

Lemma jobs_must_arrive_to_be_ready:
jobs_must_be_ready_to_execute sched → jobs_must_arrive_to_execute sched.

Furthermore, in a valid schedule, jobs must arrive to execute.

  Corollary valid_schedule_implies_jobs_must_arrive_to_execute :
    ∀ arr_seq,
      valid_schedule sched arr_seq → jobs_must_arrive_to_execute sched.

Since backlogged jobs are by definition ready, any backlogged job must have arrived.

  Corollary backlogged_implies_arrived:
    ∀ j t,
      backlogged sched j t → has_arrived j t.

Similarly, since backlogged jobs are by definition pending, any backlogged job must be incomplete.

  Lemma backlogged_implies_incomplete:
    ∀ j t,
      backlogged sched j t → ~~ completed_by sched j t.

Finally, we restate common hypotheses on the well-formedness of schedules to make their implications more easily discoverable. First, on the readiness of scheduled jobs, ...

  Lemma job_scheduled_implies_ready :
    jobs_must_be_ready_to_execute sched →
    ∀ j t,
      scheduled_at sched j t → job_ready sched j t.

... second, on the origin of scheduled jobs, and ...

  Lemma valid_schedule_jobs_come_from_arrival_sequence :
    ∀ arr_seq,
      valid_schedule sched arr_seq →
      jobs_come_from_arrival_sequence sched arr_seq.

... third, on the readiness of jobs in valid schedules.

  Lemma valid_schedule_jobs_must_be_ready_to_execute :
    ∀ arr_seq,
      valid_schedule sched arr_seq → jobs_must_be_ready_to_execute sched.

End Arrived.

In this section, we establish useful facts about arrival sequence prefixes.

Section ArrivalSequencePrefix.

Consider any kind of tasks and jobs.

  Context {Job: JobType}.
  Context {Task : TaskType}.
  Context `{JobArrival Job}.
  Context `{JobTask Job Task}.

Consider any job arrival sequence.

Variable arr_seq: arrival_sequence Job.

We begin with basic lemmas for manipulating the sequences.

Section Composition.

We show that the set of arriving jobs can be split into disjoint intervals.

    Lemma arrivals_between_cat:
      ∀ t1 t t2,
        t1 ≤ t →
        t ≤ t2 →
        arrivals_between arr_seq t1 t2 =
        arrivals_between arr_seq t1 t ++ arrivals_between arr_seq t t2.

We also prove a stronger version of the above lemma in the case of arrivals that satisfy a predicate P.

    Lemma arrivals_P_cat:
      ∀ P t t1 t2,
        t1 ≤ t < t2 →
        arrivals_between_P arr_seq P t1 t2 =
        arrivals_between_P arr_seq P t1 t ++ arrivals_between_P arr_seq P t t2.

The same observation applies to membership in the set of arrived jobs.

    Lemma arrivals_between_mem_cat:
      ∀ j t1 t t2,
        t1 ≤ t →
        t ≤ t2 →
        j \in arrivals_between arr_seq t1 t2 =
        (j \in arrivals_between arr_seq t1 t ++ arrivals_between arr_seq t t2 ).

We observe that we can grow the considered interval without "losing" any arrived jobs, i.e., membership in the set of arrived jobs is monotonic.

    Lemma arrivals_between_sub :
      ∀ j t1 t1' t2 t2',
        t1' ≤ t1 →
        t2 ≤ t2' →
        j \in arrivals_between arr_seq t1 t2 →
        j \in arrivals_between arr_seq t1' t2'.

  End Composition.

Next, we relate the arrival prefixes with job arrival times.

Section ArrivalTimes.

Assume that job arrival times are consistent.

Hypothesis H_consistent_arrival_times : consistent_arrival_times arr_seq.

To make the hypothesis and its implication easier to discover, we restate it as a trivial lemma.

    Lemma job_arrival_arrives_at :
      ∀ {j t},
        arrives_at arr_seq j t → job_arrival j = t.

Similarly, to simplify subsequent proofs, we restate the H_consistent_arrival_times assumption as a trivial corollary.

    Lemma job_arrival_at :
      ∀ {j t},
        j \in arrivals_at arr_seq t → job_arrival j = t.

Next, we prove that if j is a part of the arrival sequence, then the converse of the above also holds.

    Lemma job_in_arrivals_at :
      ∀ j t,
        arrives_in arr_seq j →
        job_arrival j = t →
        j \in arrivals_at arr_seq t.

To begin with actual properties, we observe that any job in the set of all arrivals between time instants t1 and t2 must arrive in the interval [t1,t2).

    Lemma job_arrival_between :
      ∀ {j t1 t2},
        j \in arrivals_between arr_seq t1 t2 → t1 ≤ job_arrival j < t2.

For convenience, we restate the left bound of the above lemma...

    Corollary job_arrival_between_ge :
      ∀ {j t1 t2},
        j \in arrivals_between arr_seq t1 t2 → t1 ≤ job_arrival j.

... as well as the right bound separately as corollaries.

    Corollary job_arrival_between_lt :
      ∀ {j t1 t2},
        j \in arrivals_between arr_seq t1 t2 → job_arrival j < t2.

Consequently, if we filter the list of arrivals in an interval [t1,t2) with an arrival-time threshold less than t1, we are left with an empty list.

    Lemma arrivals_between_filter_nil :
      ∀ t1 t2 t,
        t < t1 →
        [seq j <- arrivals_between arr_seq t1 t2 | job_arrival j < t ] = [::].

Furthermore, if we filter the list of arrivals in an interval [t1,t2) with an arrival-time threshold less than t2, we can simply discard the tail past the threshold.

    Lemma arrivals_between_filter :
      ∀ t1 t2 t,
        t ≤ t2 →
        arrivals_between arr_seq t1 t
        = [seq j <- arrivals_between arr_seq t1 t2 | job_arrival j < t ].

Next, we prove that if a job belongs to the prefix (jobs_arrived_before t), then it arrives in the arrival sequence.

    Lemma in_arrivals_implies_arrived:
      ∀ j t1 t2,
        j \in arrivals_between arr_seq t1 t2 →
        arrives_in arr_seq j.

We also prove a weaker version of the above lemma.

    Lemma in_arrseq_implies_arrives:
      ∀ t j,
        j \in arr_seq t →
        arrives_in arr_seq j.

Next, we prove that if a job belongs to the prefix (jobs_arrived_between t1 t2), then it indeed arrives between t1 and t2.

    Lemma in_arrivals_implies_arrived_between:
      ∀ j t1 t2,
        j \in arrivals_between arr_seq t1 t2 →
        arrived_between j t1 t2.

Similarly, if a job belongs to the prefix (jobs_arrived_before t), then it indeed arrives before time t.

    Lemma in_arrivals_implies_arrived_before:
      ∀ j t,
        j \in arrivals_before arr_seq t →
        arrived_before j t.

Similarly, we prove that if a job from the arrival sequence arrives before t, then it belongs to the sequence (jobs_arrived_before t).

    Lemma arrived_between_implies_in_arrivals:
      ∀ j t1 t2,
        arrives_in arr_seq j →
        arrived_between j t1 t2 →
        j \in arrivals_between arr_seq t1 t2.

Any job in arrivals between time instants t1 and t2 must arrive in the interval [t1,t2).

    Lemma job_arrival_between_P:
      ∀ j P t1 t2,
        j \in arrivals_between_P arr_seq P t1 t2 →
        t1 ≤ job_arrival j < t2.

Any job j is in the sequence arrivals_between t1 t2 given that j arrives in the interval [t1,t2).

    Lemma job_in_arrivals_between:
      ∀ j t1 t2,
        arrives_in arr_seq j →
        t1 ≤ job_arrival j →
        job_arrival j < t2 →
        j \in arrivals_between arr_seq t1 t2.

Next, we prove that if the arrival sequence doesn't contain duplicate jobs, the same applies for any of its prefixes.

    Lemma arrivals_uniq:
      arrival_sequence_uniq arr_seq →
      ∀ t1 t2, uniq (arrivals_between arr_seq t1 t2).

Also note that there can't by any arrivals in an empty time interval.

    Lemma arrivals_between_geq:
      ∀ t1 t2,
        t1 ≥ t2 →
        arrivals_between arr_seq t1 t2 = [::].

Conversely, if a job arrives, the considered interval is non-empty.

    Corollary arrivals_between_nonempty :
      ∀ t1 t2 j,
        j \in arrivals_between arr_seq t1 t2 → t1 < t2.

Given jobs j1 and j2 in arrivals_between_P arr_seq P t1 t2, the fact that j2 arrives strictly before j1 implies that j2 also belongs in the sequence arrivals_between_P arr_seq P t1 (job_arrival j1).

    Lemma arrival_lt_implies_job_in_arrivals_between_P :
      ∀ (j1 j2 : Job) (P : Job → bool) (t1 t2 : instant),
        j1 \in arrivals_between_P arr_seq P t1 t2 →
        j2 \in arrivals_between_P arr_seq P t1 t2 →
        job_arrival j2 < job_arrival j1 →
        j2 \in arrivals_between_P arr_seq P t1 (job_arrival j1).

For ease of rewriting, we establish the equivalence between a job's membership in arrivals_between and its membership in arrives_in, subject to constraints on the job's arrival time.

    Lemma job_arrival_in_bounds :
      ∀ (j : Job) (t1 t2 : instant),
        (j \in arrivals_between arr_seq t1 t2 )
        ↔ (arrives_in arr_seq j ∧ t1 ≤ job_arrival j < t2 ).

We observe that, by construction, the sequence of arrivals is sorted by arrival times. To this end, we first define the order relation.

Definition by_arrival_times (j1 j2 : Job) : bool := job_arrival j1 ≤ job_arrival j2.

Trivially, the arrivals at any one point in time are ordered w.r.t. arrival times.

    Lemma arrivals_at_sorted :
      ∀ t,
        sorted by_arrival_times (arrivals_at arr_seq t).

By design, the list of arrivals in any interval is sorted.

    Lemma arrivals_between_sorted :
      ∀ t1 t2,
        sorted by_arrival_times (arrivals_between arr_seq t1 t2).

  End ArrivalTimes.

In the following section, we establish a lemma that allows splitting the arrival sequence by task.

Section ArrivalPartition.

If all jobs stem from tasks in a given task set ts...

Variable ts : seq Task.
Hypothesis H_all_jobs_from_taskset : all_jobs_from_taskset arr_seq ts.

... then we can partition the arrival sequence by task.

    Lemma arrivals_between_partitioned_by_task:
      ∀ t1 t2 j,
        (j \in arrivals_between arr_seq t1 t2 )
        = (j \in \cat_(tsk <- ts ) task_arrivals_between arr_seq tsk t1 t2 ).

  End ArrivalPartition.

End ArrivalSequencePrefix.

In this section, we establish a few auxiliary facts about the relation between the property of being scheduled and arrival predicates to facilitate automation.

Section ScheduledImpliesArrives.

Consider any type of jobs.

Context {Job : JobType}.
Context `{JobArrival Job}.

Consider any kind of processor state model, ...

Context {PState : ProcessorState Job}.

... any job arrival sequence with consistent arrivals, ....

Variable arr_seq : arrival_sequence Job.
Hypothesis H_arrival_times_are_consistent : consistent_arrival_times arr_seq.

... and any schedule of this arrival sequence ...

Variable sched : schedule PState.
Hypothesis H_jobs_come_from_arrival_sequence : jobs_come_from_arrival_sequence sched arr_seq.

... where jobs do not execute before their arrival.

Hypothesis H_jobs_must_arrive_to_execute : jobs_must_arrive_to_execute sched.

Next, consider a job j ...

Variable j : Job.

... which is scheduled at a time instant t.

Variable t : instant.
Hypothesis H_scheduled_at : scheduled_at sched j t.

Then we show that j arrives in arr_seq.

Lemma arrives_in_jobs_come_from_arrival_sequence :
arrives_in arr_seq j.

Job j has arrived by time instant t.

Lemma arrived_between_jobs_must_arrive_to_execute :
has_arrived j t.

For any future time t', job j arrives before t'.

  Lemma arrivals_before_scheduled_at :
    ∀ t',
      t < t' →
      j \in arrivals_before arr_seq t'.

Similarly, job j arrives up to time t' for any t' such that t ≤ t'.

  Lemma arrivals_up_to_scheduled_at :
    ∀ t',
      t ≤ t' →
      j \in arrivals_up_to arr_seq t'.

End ScheduledImpliesArrives.

We add some of the above lemmas to the "Hint Database" basic_rt_facts, so the auto tactic will be able to use them.

Global Hint Resolve
       any_ready_job_is_pending
       arrivals_before_scheduled_at
       arrivals_uniq
       arrived_between_implies_in_arrivals
       arrived_between_jobs_must_arrive_to_execute
       arrives_in_jobs_come_from_arrival_sequence
       backlogged_implies_arrived
       job_scheduled_implies_ready
       jobs_must_arrive_to_be_ready
       jobs_must_arrive_to_be_ready
       ready_implies_arrived
       valid_schedule_implies_jobs_must_arrive_to_execute
       valid_schedule_jobs_come_from_arrival_sequence
       valid_schedule_jobs_must_be_ready_to_execute
       uniq_valid_arrival
       consistent_times_valid_arrival
       job_arrival_arrives_at
       job_in_arrivals_between
  : basic_rt_facts.