Project Page Index Table of Contents

# Library prosa.analysis.facts.model.service_of_jobs

Require Export prosa.model.aggregate.workload.
Require Export prosa.model.aggregate.service_of_jobs.
Require Export prosa.analysis.facts.behavior.completion.
Require Export prosa.analysis.facts.busy_interval.quiet_time.
Require Export prosa.analysis.facts.model.uniprocessor.

# Lemmas about Service Received by Sets of Jobs

In this file, we establish basic facts about the service received by sets of jobs.
To begin with, we provide some basic properties of service of a set of jobs in case of a generic scheduling model.
Section GenericModelLemmas.
Consider any type of tasks ...
Context {Task : TaskType}.
... and any type of jobs associated with these tasks.
Context {Job : JobType}.
Context `{JobTask Job Task}.
Context `{JobArrival Job}.
Context `{JobCost 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.
... 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.
Let P be any predicate over jobs.
Variable P : pred Job.
We show that the total service of jobs released in a time interval `[t1,t2)` during `[t1,t2)` is equal to the sum of: (1) the total service of jobs released in time interval `[t1, t)` during time `[t1, t)` (2) the total service of jobs released in time interval `[t1, t)` during time `[t, t2)` and (3) the total service of jobs released in time interval `[t, t2)` during time `[t, t2)`.
Lemma service_of_jobs_cat_scheduling_interval :
∀ t1 t2 t,
t1 ≤ t ≤ t2 →
service_of_jobs sched P (arrivals_between arr_seq t1 t2) t1 t2
= service_of_jobs sched P (arrivals_between arr_seq t1 t) t1 t
+ service_of_jobs sched P (arrivals_between arr_seq t1 t) t t2
+ service_of_jobs sched P (arrivals_between arr_seq t t2) t t2.
Proof.
move ⇒ t1 t2 t /andP [GEt LEt].
rewrite (arrivals_between_cat _ _ t) //.
rewrite {1}/service_of_jobs big_cat //=.
rewrite exchange_big //= (@big_cat_nat _ _ _ t) //=;
rewrite [in X in X + _ + _]exchange_big //= [in X in _ + X + _]exchange_big //=.
apply/eqP; rewrite -!addnA eqn_add2l eqn_add2l.
rewrite exchange_big //= (@big_cat_nat _ _ _ t) //= [in X in _ + X]exchange_big //=.
rewrite -[service_of_jobs _ _ _ _ _]add0n /service_of_jobs eqn_add2r.
rewrite big_nat_cond big1 //.
move ⇒ x /andP [/andP [GEi LTi] _].
rewrite big_seq_cond big1 //.
move ⇒ j /andP [ARR Ps].
apply: service_before_job_arrival_zero ⇒ //.
eapply in_arrivals_implies_arrived_between in ARR; eauto 2.
by move: ARR ⇒ /andP [N1 N2]; apply leq_trans with t.
Qed.
We show that the total service of jobs released in a time interval `[t1, t2)` during `[t, t2)` is equal to the sum of: (1) the total service of jobs released in a time interval `[t1, t)` during `[t, t2)` and (2) the total service of jobs released in a time interval `[t, t2)` during `[t, t2)`.
Lemma service_of_jobs_cat_arrival_interval :
∀ t1 t2 t,
t1 ≤ t ≤ t2 →
service_of_jobs sched P (arrivals_between arr_seq t1 t2) t t2
= service_of_jobs sched P (arrivals_between arr_seq t1 t) t t2
+ service_of_jobs sched P (arrivals_between arr_seq t t2) t t2.
Proof.
move ⇒ t1 t2 t /andP [GEt LEt].
apply/eqP;rewrite eq_sym; apply/eqP.
rewrite [in X in _ = X](arrivals_between_cat _ _ t) //.
by rewrite {3}/service_of_jobs -big_cat //=.
Qed.
Section ArbitraryInterval.
In the following, we consider an arbitrary sequence of jobs jobs.
Variable jobs : seq Job.
Also, consider an interval `[t1, t2)`...
Variable t1 t2 : instant.
...and two additional predicates P1 and P2.
Variable P1 P2 : pred Job.
For brevity, in the following comments we denote a subset of jobs satisfying a predicate P by {jobs | P}.
First, we prove that the service received by {jobs | P1} can be split into: (1) the service received by the subset {jobs | P1 ∧ P2} and (2) the service received by the subset {jobs | P1 ∧ ¬ P2}.
Lemma service_of_jobs_case_on_pred :
service_of_jobs sched P1 jobs t1 t2
= service_of_jobs sched (fun j ⇒ P1 j && P2 j) jobs t1 t2
+ service_of_jobs sched (fun j ⇒ P1 j && ~~ P2 j) jobs t1 t2.
Proof.
rewrite /service_of_jobs big_mkcond //=.
rewrite [in X in _ = X + _]big_mkcond //=.
rewrite [in X in _ = _ + X]big_mkcond //=.
rewrite -big_split; apply eq_big_seq; intros j IN.
by destruct (P1 _), (P2 _); simpl; lia.
Qed.
We show that the service received by {jobs | P} is equal to the difference between the total service received by jobs and the service of {jobs | ¬ P}.
Lemma service_of_jobs_negate_pred :
service_of_jobs sched P jobs t1 t2
= total_service_of_jobs_in sched jobs t1 t2
- service_of_jobs sched (fun j ⇒ ~~ P j) jobs t1 t2.
Proof.
rewrite /total_service_of_jobs_in /service_of_jobs.
rewrite big_mkcond [in X in _ = X - _]big_mkcond [in X in _ = _ - X]big_mkcond //=.
rewrite -sumnB; last by move⇒ j _; case: (P j).
apply: eq_big_seq ⇒ j IN.
by case: (P j) ⇒ //=; lia.
Qed.
We show that service_of_jobs is monotone with respect to the predicate. That is, given the fact ∀ j ∈ jobs: P1 j ==> P2 j, we show that the service of {jobs | P1} is bounded by the service of {jobs | P2}.
Lemma service_of_jobs_pred_impl :
(∀ j : Job, j \in jobs → P1 j → P2 j) →
service_of_jobs sched P1 jobs t1 t2 ≤ service_of_jobs sched P2 jobs t1 t2.
Proof. by intros IMPL; apply leq_sum_seq_pred; eauto. Qed.
Similarly, we show that if P1 is equivalent to P2, then the service of {jobs | P1} is equal to the service of {jobs | P2}.
Lemma service_of_jobs_equiv_pred :
{in jobs, P1 =1 P2} →
service_of_jobs sched P1 jobs t1 t2 = service_of_jobs sched P2 jobs t1 t2.
Proof.
intros × EQUIV.
rewrite /service_of_jobs !big_mkcond [in X in _ = X]big_mkcond //=; apply: eq_big_seq.
intros j IN; specialize (EQUIV j IN); simpl in EQUIV; rewrite EQUIV; clear EQUIV.
by case: (P2 j) ⇒ //.
Qed.
Next, we show an auxiliary lemma that allows us to change the order of summation.
Recall that service_of_jobs is defined as a sum over all jobs in jobs of `[service_during j [t1,t2)]`. We show that service_of_jobs over an interval `[t1,t2)` is equal to the sum over individual time instances (in `[t1,t2)`) of service_of_jobs_at.
In other words, we show that `[∑_{j ∈ jobs} ∑_{t \in [t1,t2)} service of j at t]` is equal to `[∑_{t \in [t1,t2)} ∑_{j ∈ jobs} service of j at t]`.
Lemma service_of_jobs_sum_over_time_interval :
service_of_jobs sched P jobs t1 t2
= \sum_(t1 ≤ t < t2) service_of_jobs_at sched P jobs t.
Proof. by apply exchange_big. Qed.
We show that service of {jobs | false} is equal to 0.
Lemma service_of_jobs_pred0 :
service_of_jobs sched pred0 jobs t1 t2 = 0.
Proof. by apply big_pred0. Qed.
More generally, if none of the jobs inside jobs is scheduled at time t or satisfies P, then total service of jobs at time t is equal to 0.
Lemma service_of_jobs_nsched_or_unsat :
∀ (t : instant),
(∀ j, j \in jobs → ~~ (P j && scheduled_at sched j t)) →
service_of_jobs_at sched P jobs t = 0.
Proof.
intros ? ALL.
elim: jobs ALL ⇒ [|a l IHl] ALL.
- by rewrite /service_of_jobs_at big_nil.
- feed IHl.
{ by intros j' IN; apply ALL; rewrite in_cons; apply/orP; right. }
rewrite /service_of_jobs_at big_cons; rewrite /service_of_jobs_at in IHl.
destruct (P a) eqn: Pa ⇒ [|//].
rewrite IHl addn0.
specialize (ALL a); feed ALL.
{ by rewrite in_cons; apply/orP; left. }
rewrite Pa Bool.andb_true_l in ALL.
by apply not_scheduled_implies_no_service.
Qed.
The amount of service accrued in an empty interval is trivially zero.
Lemma service_of_jobs_geq :
t1 ≥ t2 →
service_of_jobs sched P jobs t1 t2 = 0.
Proof.
move⇒ LEQ.
rewrite /service_of_jobs; apply/eqP.
rewrite sum_nat_seq_eq0; apply/allP ⇒ j IN.
apply/implyP ⇒ Pj.
by apply/eqP/big_geq.
Qed.
End ArbitraryInterval.
When considering the service accumulated by bunch of jobs in an interval `[t1, t2]`, the total amount of service can be split into the service received during `[t1, t2)` and the service received at the last point in time t2.
Lemma service_of_jobs_cat_last :
∀ js t1 t2,
t1 ≤ t2 →
service_of_jobs sched P js t1 t2.+1
= service_of_jobs sched P js t1 t2
+ service_of_jobs_at sched P js t2.
Proof.
move⇒ js t1 t2 LEQ.
rewrite !service_of_jobs_sum_over_time_interval.
by rewrite big_nat_recr.
Qed.
End GenericModelLemmas.
In this section, we prove a lemma about the sum of service with different predicates over a fixed time interval.
Section HEPService.
Consider any type of jobs.
Context {Job : JobType}.
Context `{JobArrival Job}.
Context `{JobCost Job}.
Consider any kind of processor state model, ...
Context {PState : ProcessorState Job}.
... any valid arrival sequence, ...
Variable arr_seq : arrival_sequence Job.
Hypothesis H_valid_arrival_sequence : valid_arrival_sequence arr_seq.
... and any schedule of this arrival sequence ...
Variable sched : schedule PState.
... where jobs do not execute before their arrival.
Hypothesis H_jobs_must_arrive_to_execute : jobs_must_arrive_to_execute sched.
Consider a JLFP policy that indicates a higher-or-equal priority relation and assume that the relation is reflexive.
Context {JLFP : JLFP_policy Job}.
Hypothesis H_priority_is_reflexive : reflexive_job_priorities JLFP.
Consider an interval `[t1, t2)` ...
Variables t1 t2 : instant.
... and a job j arriving no earlier than t1.
Variable j : Job.
Hypothesis H_arrives : arrives_in arr_seq j.
Hypothesis H_t1_le_j_arr : t1 ≤ job_arrival j.
We prove that the sum of the service during `[t1, t2)` of job j and the service of higher-or-equal priority jobs distinct from j during `[t1, t2)` is equal to the service of higher-or-equal priority jobs in `[t1, t2)`.
Lemma service_plus_ahep_eq_service_hep :
service_during sched j t1 t2 + service_of_other_hep_jobs arr_seq sched j t1 t2
= service_of_hep_jobs arr_seq sched j t1 t2.
Proof.
have EQ: ∀ a b c, b ≤ c → a = c - b → a + b = c by lia.
apply: EQ; first by apply service_of_jobs_pred_impl ⇒ s IN2 /andP [AHEP _].
rewrite /service_of_other_hep_jobs /service_of_hep_jobs.
erewrite service_of_jobs_case_on_pred with (P2 := fun jhp ⇒ jhp == j).
have → : ∀ a b, a + b - b = a by lia.
have [LE|LT] := leqP t2 (job_arrival j).
{ apply eq_trans with 0; last symmetry.
{ by apply: cumulative_service_before_job_arrival_zero ⇒ //. }
{ rewrite /service_of_jobs // big1_seq // ⇒ s /andP [/andP [_ /eqP EQ] IN]; subst s.
by apply: cumulative_service_before_job_arrival_zero ⇒ //. }
}
{ rewrite /service_of_jobs; erewrite big_pred1_seq ⇒ //.
{ move ⇒ j'; rewrite /pred1 //=.
have [A|B] := eqVneq j' j; last by rewrite andbF.
by rewrite andbT; subst; apply H_priority_is_reflexive.
}
}
Qed.
End HEPService.
In this section, we prove some properties about service of sets of jobs for unit-service processor models.
Section UnitServiceModelLemmas.
Consider any type of tasks ...
Context {Task : TaskType}.
... and any type of jobs associated with these tasks.
Context {Job : JobType}.
Context `{JobTask Job Task}.
Context `{JobArrival Job}.
Context `{JobCost Job}.
Consider any kind of unit-service processor state model.
Context {PState : ProcessorState Job}.
Hypothesis H_unit_service_proc_model : unit_service_proc_model PState.
Consider any arrival sequence with consistent arrivals.
Variable arr_seq : arrival_sequence Job.
Hypothesis H_arrival_times_are_consistent : consistent_arrival_times arr_seq.
Next, consider any unit-service 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 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.
Let P be any predicate over jobs.
Variable P : pred Job.
First, we prove that the service received by any set of jobs is upper-bounded by the corresponding workload.
Lemma service_of_jobs_le_workload :
∀ (jobs : seq Job) (t1 t2 : instant),
service_of_jobs sched P jobs t1 t2 ≤ workload_of_jobs P jobs.
Proof.
intros jobs t1 t2.
apply leq_sum; intros j _.
by apply cumulative_service_le_job_cost.
Qed.
In this section, we introduce a connection between the cumulative service, cumulative workload, and completion of jobs.
Section WorkloadServiceAndCompletion.
Consider an arbitrary time interval `[t1, t2)`.
Variables t1 t2 : instant.
Let jobs be a set of all jobs arrived during `[t1, t2)`.
Let jobs := arrivals_between arr_seq t1 t2.
Next, we consider some time instant t_compl.
Variable t_compl : instant.
And state the proposition that all jobs are completed by time t_compl. Next we show that this proposition is equivalent to the fact that workload of jobs = service of jobs.
Let all_jobs_completed_by t_compl :=
∀ j, j \in jobs → P j → completed_by sched j t_compl.
First, we prove that if the workload of jobs is equal to the service of jobs, then any job in jobs is completed by time t_compl.
Lemma workload_eq_service_impl_all_jobs_have_completed :
workload_of_jobs P jobs = service_of_jobs sched P jobs t1 t_compl →
all_jobs_completed_by t_compl.
Proof.
unfold jobs; intros EQ j ARR Pj; move: (ARR) ⇒ ARR2.
apply in_arrivals_implies_arrived_between in ARR ⇒ [|//].
move: ARR ⇒ /andP [T1 T2].
have F1: ∀ a b, (a < b) || (a ≥ b).
{ by move⇒ a b; destruct (a < b) eqn:EQU; apply/orP;
[by left |right]; apply negbT in EQU; rewrite leqNgt. }
move: (F1 t_compl t1) ⇒ /orP [LT | GT].
- rewrite /service_of_jobs /service_during in EQ.
rewrite exchange_big big_geq //= in EQ.
rewrite /workload_of_jobs in EQ.
rewrite (big_rem j) ?Pj //= in EQ.
move: EQ ⇒ /eqP; rewrite addn_eq0 ⇒ /andP [CZ _].
unfold completed_by, service.completed_by.
by move: CZ ⇒ /eqP CZ; rewrite CZ.
- unfold workload_of_jobs, service_of_jobs in EQ; unfold completed_by, service.completed_by.
rewrite /service -(service_during_cat _ _ _ t1); last by apply/andP; split.
rewrite cumulative_service_before_job_arrival_zero // add0n.
apply: eq_leq; have /esym/eqP := EQ; rewrite eq_sum_leq_seq.
{ move⇒ /allP/(_ j) + /ltac:(apply/esym/eqP); apply.
by rewrite mem_filter Pj. }
by intros; apply cumulative_service_le_job_cost; eauto.
Qed.
And vice versa, the fact that any job in jobs is completed by time t_compl implies that the workload of jobs is equal to the service of jobs.
Lemma all_jobs_have_completed_impl_workload_eq_service :
all_jobs_completed_by t_compl →
workload_of_jobs P jobs = service_of_jobs sched P jobs t1 t_compl.
Proof.
unfold jobs; intros COMPL.
have F: ∀ j t, t ≤ t1 → j \in arrivals_between arr_seq t1 t2 → service_during sched j 0 t = 0.
{ intros j t LE ARR.
eapply in_arrivals_implies_arrived_between in ARR; eauto 2; move: ARR ⇒ /andP [GE LT].
eapply cumulative_service_before_job_arrival_zero; eauto 2.
by apply leq_trans with t1.
}
destruct (t_compl ≤ t1) eqn:EQ.
- unfold service_of_jobs. unfold service_during.
rewrite exchange_big //=.
rewrite big_geq ⇒ [|//].
rewrite /workload_of_jobs big1_seq //.
move ⇒ j /andP [Pj ARR].
specialize (COMPL _ ARR Pj).
rewrite <- F with (j := j) (t := t_compl) ⇒ //.
apply/eqP; rewrite eqn_leq; apply/andP; split.
+ by apply COMPL.
+ by apply service_at_most_cost.
- apply/eqP; rewrite eqn_leq; apply/andP; split; first last.
+ by apply service_of_jobs_le_workload.
+ rewrite /workload_of_jobs big_seq_cond [X in _ ≤ X]big_seq_cond.
rewrite leq_sum // ⇒ j /andP [ARR Pj].
specialize (COMPL _ ARR Pj).
rewrite -[service_during _ _ _ _ ]add0n -(F j t1) //= -(big_cat_nat) //=.
move: EQ =>/negP /negP; rewrite -ltnNge ⇒ EQ.
by apply ltnW.
Qed.
Using the lemmas above, we prove the equivalence.
Corollary all_jobs_have_completed_equiv_workload_eq_service :
all_jobs_completed_by t_compl ↔
workload_of_jobs P jobs = service_of_jobs sched P jobs t1 t_compl.
Proof.
split.
- by apply all_jobs_have_completed_impl_workload_eq_service.
- by apply workload_eq_service_impl_all_jobs_have_completed.
Qed.
End WorkloadServiceAndCompletion.
End UnitServiceModelLemmas.
In this section, we prove some properties about service of sets of jobs for unit-service uniprocessor models.
Section UnitServiceUniProcessorModelLemmas.
Consider any type of tasks ...
Context {Task : TaskType}.
... and any type of jobs associated with these tasks.
Context {Job : JobType}.
Context `{JobTask Job Task}.
Context `{JobArrival Job}.
Context `{JobCost Job}.
Consider any kind of unit-service uniprocessor state model.
Context {PState : ProcessorState Job}.
Hypothesis H_unit_service_proc_model : unit_service_proc_model PState.
Hypothesis H_uniprocessor_model : uniprocessor_model PState.
Consider any arrival sequence with consistent arrivals.
Variable arr_seq : arrival_sequence Job.
Hypothesis H_arrival_times_are_consistent : consistent_arrival_times arr_seq.
Next, consider any unit-service uni-processor 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 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.
Let P be any predicate over jobs.
Variable P : pred Job.
In this section, we prove that the service received by any set of jobs is upper-bounded by the corresponding interval length.
Section ServiceOfJobsIsBoundedByLength.
Let jobs denote any set of jobs.
Variable jobs : seq Job.
Hypothesis H_no_duplicate_jobs : uniq jobs.
We prove that the overall service of jobs at a single time instant is at most 1.
Lemma service_of_jobs_le_1 :
∀ t, service_of_jobs_at sched P jobs t ≤ 1.
Proof.
intros t.
eapply leq_trans.
{ by apply leq_sum_seq_pred with (P2 := predT); intros. }
simpl; elim: jobs H_no_duplicate_jobs ⇒ [|j js IHjs] uniq_js.
- by rewrite big_nil.
- feed IHjs; first by move: uniq_js; rewrite cons_uniq ⇒ /andP [_ U].
rewrite big_cons.
destruct (service_is_zero_or_one H_unit_service_proc_model sched j t) as [Z | O].
+ by rewrite Z (leqRW IHjs).
+ have → : \sum_(j <- js) service_in j (sched t) = 0; last by rewrite O.
have POS: service_at sched j t > 0 by rewrite O.
apply service_at_implies_scheduled_at in POS.
apply/eqP; rewrite big_seq big1 //; intros j' IN.
apply/eqP; rewrite -leqn0 leqNgt.
eapply contra with (b := scheduled_at sched j' t);
first apply service_at_implies_scheduled_at.
apply/negP; intros SCHED.
specialize (H_uniprocessor_model _ _ _ _ POS SCHED); subst j'.
by move: uniq_js; rewrite cons_uniq ⇒ /andP [/negP NIN _].
Qed.
Next, we prove that the service received by those jobs is no larger than their workload.
Corollary service_of_jobs_le_length_of_interval :
∀ (t : instant) (Δ : duration),
service_of_jobs sched P jobs t (t + Δ) ≤ Δ.
Proof.
move⇒ t Δ.
have EQ: \sum_(t ≤ x < t + Δ) 1 = Δ.
{ by rewrite big_const_nat iter_addn mul1n addn0 -{2}[t]addn0 subnDl subn0. }
rewrite -{2}EQ {EQ}.
rewrite /service_of_jobs/service_during/service_at exchange_big //=.
rewrite leq_sum //.
move ⇒ t' _.
by apply service_of_jobs_le_1.
Qed.
The same holds for two time instants.
Corollary service_of_jobs_le_length_of_interval' :
∀ (t1 t2 : instant),
service_of_jobs sched P jobs t1 t2 ≤ t2 - t1.
Proof.
move⇒ t1 t2.
have <-: \sum_(t1 ≤ x < t2) 1 = t2 - t1.
{ by rewrite big_const_nat iter_addn mul1n addn0. }
rewrite /service_of_jobs exchange_big //=.
rewrite leq_sum //.
move ⇒ t' _.
have SE := service_of_jobs_le_1 t'.
eapply leq_trans; last by eassumption.
by rewrite leq_sum.
Qed.
End ServiceOfJobsIsBoundedByLength.
Let us consider the special case where the processor also guarantees ideal progress.
Section IdealProgress.
Suppose we have an ideal unit-speed processor.
Hypothesis H_ideal_progress_model : ideal_progress_proc_model PState.
Let js denote any set of jobs.
Variable js : seq Job.
Hypothesis H_no_duplicate_jobs : uniq js.
On a unit-speed processor, if we know that a job in the given set js is scheduled, then the total service accrued by js at this point in time increases by exactly one time unit.
Lemma service_of_jobs_at_scheduled1 :
∀ t,
(∃ j, j \in js ∧ scheduled_at sched j t ∧ P j) →
service_of_jobs_at sched P js t = 1.
Proof.
move⇒ t [j [IN [SCHED Pj]]].
have NSCHED: ∀ j', j' != j → service_at sched j' t = 0.
{ move⇒ j' /[1! eq_sym] NEQ.
rewrite -no_service_not_scheduled //.
by apply: scheduled_job_at_neq. }
rewrite /service_of_jobs_at (bigID (fun j' ⇒ j' == j )) /=.
have /eqP ->: \sum_(i <- js | P i && (i != j)) service_at sched i t == 0.
{ rewrite sum_nat_seq_eq0.
apply/allP ⇒ j' IN'.
apply/implyP ⇒ /andP[Pj' NEQ].
by apply/eqP/NSCHED. }
rewrite addn0.
have ->: \sum_(i <- js | P i && (i == j)) service_at sched i t
= \sum_(i <- [:: j] | P i && (i == j)) service_at sched i t.
{ rewrite -[LHS]big_filter -[RHS]big_filter.
apply: congr_big ⇒ //.
rewrite !filter_predI !filter_pred1_uniq //.
exact: mem_head. }
rewrite big_mkcond big_seq1 Pj eq_refl //=.
exact: unit_service_at1.
Qed.
When considering the amount of service accrued by a set of jobs during some interval, if we know that at each point some job from the set is scheduled, then the total amount of service accrued (on a unit-speed processor) in total by the set of jobs is equal to the length of the interval.
Lemma service_of_jobs_always_scheduled :
∀ t1 t2,
(∀ t, t1 ≤ t < t2 → ∃ j, j \in js ∧ scheduled_at sched j t ∧ P j) →
service_of_jobs sched P js t1 t2 = t2 - t1.
Proof.
move⇒ t1 t2 SCHED.
elim: t2 SCHED ⇒ [|t2 IH SCHED];
first by rewrite service_of_jobs_geq; lia.
have [LEQ|LT] := leqP t1 t2;
last by rewrite service_of_jobs_geq; lia.
rewrite service_of_jobs_cat_last // IH;
last by move⇒ t /andP[LO HI]; apply: SCHED; lia.
by rewrite service_of_jobs_at_scheduled1 //; [|apply: SCHED]; lia.
Qed.
End IdealProgress.
In this section, we prove a relation between a predicate defined on a set of jobs and the total service of these jobs.
Section PredServedEqService.
Assume that the arrival sequence does not contain duplicate arrivals.
Hypothesis H_arrival_sequence_is_a_set : arrival_sequence_uniq arr_seq.
Consider a JLFP-policy that indicates a higher-or-equal priority relation.
Context {JLFP : JLFP_policy Job}.
Consider a job j.
Variable j : Job.
Hypothesis H_j_arrives : arrives_in arr_seq j.
We consider an arbitrary time interval `[t1, t)` that starts with a quiet time.
Variable t1 t : instant.
Hypothesis H_quiet_time : quiet_time arr_seq sched j t1.
We prove that the number of points in the interval that satisfy the predicate ∃ j ∈ served jobs: P j is equal to the total service of all jobs that satisfy P.
Note that this lemma uses served_jobs_at instead of its uniprocessor variant served_job_at. This is done on purpose so that this lemma fits better with abstract functions and predicates defined in /analysis/abstract/... since such functions are usually defined on a general (not necessarily uniprocessor) class of processor models.
Lemma cumulative_pred_served_eq_service :
(∀ j', P j' → hep_job j' j) →
\sum_(t1 ≤ t' < t) has P (served_jobs_at arr_seq sched t')
= service_of_jobs sched P (arrivals_between arr_seq t1 t) t1 t.
Proof.
move ⇒ Phep.
rewrite [RHS]exchange_big /=; apply: eq_big_nat ⇒ x /andP[t1lex xltt].
have L (js : seq Job) (UNIQ : uniq js):
\sum_(i <- js | P i) service_at sched i x
= has (fun j ⇒ (P j) && (receives_service_at sched j x)) js.
{ clear xltt t1lex Phep.
have L : ∀ (n : nat) (b : bool), (b → n = 1) → (~~ b → n = 0) → (n = b)
by clear ⇒ n [] A B; [rewrite A | rewrite B].
apply: L.
{ move⇒ /hasP [jo IN /andP [Pjo SERVjo]].
apply/eqP; rewrite eqn_leq; apply/andP; split.
- by apply service_of_jobs_le_1 ⇒ //.
- by rewrite sum_nat_gt0; apply/hasP; ∃ jo ⇒ //; rewrite mem_filter IN Pjo. }
{ move⇒ /hasPn ALL; rewrite big1_seq // ⇒ jo /andP [Pjo IN].
move: (ALL _ IN); rewrite negb_and ⇒ /orP [A | B]; first by rewrite Pjo in A.
by move: B; rewrite /receives_service_at -leqNgt leqn0 ⇒ /eqP →. } }
rewrite L; clear L; last by apply arrivals_uniq.
have L :
∀ (X : Type) (P Q : pred X) (xs : seq X),
has (fun x ⇒ P x && Q x) xs = has P ([ seq x <- xs | Q x]).
{ clear. move ⇒ X P Q xs; induction xs as [ | x xs IHxs]; first by done.
by rewrite //= IHxs; destruct (P x) eqn:Px, (Q x) eqn:Qx; rewrite //= ?Px ?Qx. }
rewrite -L; clear L; f_equal.
rewrite /arrivals_up_to (arrivals_between_cat _ _ t1); [ | lia | lia ].
rewrite has_cat -[RHS]orFb; f_equal.
- apply/eqP; rewrite eqbF_neg; apply/hasPn ⇒ jo IN; apply/negP ⇒ /andP [Pjo SERV].
apply service_at_implies_scheduled_at, scheduled_implies_not_completed in SERV ⇒ //.
move: SERV ⇒ /negP SERV; apply:SERV.
(eapply completion_monotonic; last apply: H_quiet_time) ⇒ //.
+ by apply: in_arrivals_implies_arrived.
+ by apply: job_arrival_between_lt.
- rewrite [in RHS](arrivals_between_cat _ _ x.+1); [ | lia | lia ].
rewrite has_cat -[LHS]orbF; f_equal; symmetry.
apply/eqP; rewrite eqbF_neg; apply/hasPn ⇒ jo IN; apply/negP ⇒ /andP [Pjo SERV].
apply service_at_implies_scheduled_at in SERV.
apply H_jobs_must_arrive_to_execute in SERV.
apply job_arrival_between_ge in IN ⇒ //.
by move: IN SERV; rewrite /has_arrived; lia.
Qed.
End PredServedEqService.
End UnitServiceUniProcessorModelLemmas.