Library prosa.classic.model.schedule.uni.workload
Require Import prosa.classic.util.all.
Require Import prosa.classic.model.time prosa.classic.model.arrival.basic.task prosa.classic.model.arrival.basic.job prosa.classic.model.arrival.basic.arrival_sequence
prosa.classic.model.priority.
From mathcomp Require Import ssreflect ssrbool eqtype ssrnat seq fintype bigop.
Module Workload.
Import Time ArrivalSequence Priority.
(* In this section, we define the notion of workload for sets of jobs. *)
Section WorkloadDefs.
Context {Task: eqType}.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_cost: Job → time.
Variable job_task: Job → Task.
(* Consider any job arrival sequence... *)
Variable arr_seq: arrival_sequence Job.
(* ...and any (finite) set of jobs. *)
Variable jobs: seq Job.
(* First, we define the workload for generic sets of jobs. *)
Section WorkloadOfJobs.
(* Given any predicate over Jobs, ... *)
Variable P: Job → bool.
(* ...we define the total workload of the jobs that satisfy such a predicate. *)
Definition workload_of_jobs := \sum_(j <- jobs | P j) job_cost j.
End WorkloadOfJobs.
(* Then, we define the workload of tasks with higher or equal priority
under FP policies. *)
Section PerTaskPriority.
(* Consider any FP policy that indicates whether a task has
higher or equal priority. *)
Variable higher_eq_priority: FP_policy Task.
(* Let tsk be the task to be analyzed. *)
Variable tsk: Task.
(* Recall the notion of a job of higher or equal priority. *)
Let of_higher_or_equal_priority j :=
higher_eq_priority (job_task j) tsk.
(* Then, we define the workload of all jobs of tasks with
higher-or-equal priority than tsk. *)
Definition workload_of_higher_or_equal_priority_tasks :=
workload_of_jobs of_higher_or_equal_priority.
End PerTaskPriority.
(* Then, we define the workload of jobs with higher or equal priority
under JLFP policies. *)
Section PerJobPriority.
(* Consider any JLFP policy that indicates whether a job has
higher or equal priority. *)
Variable higher_eq_priority: JLFP_policy Job.
(* Let j be the job to be analyzed. *)
Variable j: Job.
(* Recall the notion of a job of higher or equal priority. *)
Let of_higher_or_equal_priority j_hp := higher_eq_priority j_hp j.
(* Then, we define the workload of higher or equal priority of all jobs
with higher-or-equal priority than j. *)
Definition workload_of_higher_or_equal_priority_jobs :=
workload_of_jobs of_higher_or_equal_priority.
End PerJobPriority.
End WorkloadDefs.
(* We also define the workload of a task. *)
Section TaskWorkload.
Context {Task: eqType}.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_cost: Job → time.
Variable job_task: Job → Task.
(* Consider any job arrival sequence. *)
Variable arr_seq: arrival_sequence Job.
(* Let tsk be the task to be analyzed. *)
Variable tsk: Task.
(* Recall the notion of a job of task tsk. *)
Let of_task_tsk j := job_task j == tsk.
(* We define the task workload as the workload of jobs of task tsk. *)
Definition task_workload jobs := workload_of_jobs job_cost jobs of_task_tsk.
(* Next, we recall the definition of the task workload in interval t1, t2). *)
Definition task_workload_between (t1 t2: time) :=
task_workload (jobs_arrived_between arr_seq t1 t2).
End TaskWorkload.
(* In this section, we prove a few basic lemmas about the workload. *)
Section BasicLemmas.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_cost: Job → time.
(* Consider any job arrival sequence... *)
Variable arr_seq: arrival_sequence Job.
(* For simplicity, let's define some local names. *)
Let arrivals_between := jobs_arrived_between arr_seq.
(* We prove that workload can be splited into two parts. *)
Lemma workload_of_jobs_cat:
∀ t t1 t2 P,
t1 ≤ t ≤ t2 →
workload_of_jobs job_cost (arrivals_between t1 t2) P =
workload_of_jobs job_cost (arrivals_between t1 t) P
+ workload_of_jobs job_cost (arrivals_between t t2) P.
End BasicLemmas.
End Workload.
Require Import prosa.classic.model.time prosa.classic.model.arrival.basic.task prosa.classic.model.arrival.basic.job prosa.classic.model.arrival.basic.arrival_sequence
prosa.classic.model.priority.
From mathcomp Require Import ssreflect ssrbool eqtype ssrnat seq fintype bigop.
Module Workload.
Import Time ArrivalSequence Priority.
(* In this section, we define the notion of workload for sets of jobs. *)
Section WorkloadDefs.
Context {Task: eqType}.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_cost: Job → time.
Variable job_task: Job → Task.
(* Consider any job arrival sequence... *)
Variable arr_seq: arrival_sequence Job.
(* ...and any (finite) set of jobs. *)
Variable jobs: seq Job.
(* First, we define the workload for generic sets of jobs. *)
Section WorkloadOfJobs.
(* Given any predicate over Jobs, ... *)
Variable P: Job → bool.
(* ...we define the total workload of the jobs that satisfy such a predicate. *)
Definition workload_of_jobs := \sum_(j <- jobs | P j) job_cost j.
End WorkloadOfJobs.
(* Then, we define the workload of tasks with higher or equal priority
under FP policies. *)
Section PerTaskPriority.
(* Consider any FP policy that indicates whether a task has
higher or equal priority. *)
Variable higher_eq_priority: FP_policy Task.
(* Let tsk be the task to be analyzed. *)
Variable tsk: Task.
(* Recall the notion of a job of higher or equal priority. *)
Let of_higher_or_equal_priority j :=
higher_eq_priority (job_task j) tsk.
(* Then, we define the workload of all jobs of tasks with
higher-or-equal priority than tsk. *)
Definition workload_of_higher_or_equal_priority_tasks :=
workload_of_jobs of_higher_or_equal_priority.
End PerTaskPriority.
(* Then, we define the workload of jobs with higher or equal priority
under JLFP policies. *)
Section PerJobPriority.
(* Consider any JLFP policy that indicates whether a job has
higher or equal priority. *)
Variable higher_eq_priority: JLFP_policy Job.
(* Let j be the job to be analyzed. *)
Variable j: Job.
(* Recall the notion of a job of higher or equal priority. *)
Let of_higher_or_equal_priority j_hp := higher_eq_priority j_hp j.
(* Then, we define the workload of higher or equal priority of all jobs
with higher-or-equal priority than j. *)
Definition workload_of_higher_or_equal_priority_jobs :=
workload_of_jobs of_higher_or_equal_priority.
End PerJobPriority.
End WorkloadDefs.
(* We also define the workload of a task. *)
Section TaskWorkload.
Context {Task: eqType}.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_cost: Job → time.
Variable job_task: Job → Task.
(* Consider any job arrival sequence. *)
Variable arr_seq: arrival_sequence Job.
(* Let tsk be the task to be analyzed. *)
Variable tsk: Task.
(* Recall the notion of a job of task tsk. *)
Let of_task_tsk j := job_task j == tsk.
(* We define the task workload as the workload of jobs of task tsk. *)
Definition task_workload jobs := workload_of_jobs job_cost jobs of_task_tsk.
(* Next, we recall the definition of the task workload in interval t1, t2). *)
Definition task_workload_between (t1 t2: time) :=
task_workload (jobs_arrived_between arr_seq t1 t2).
End TaskWorkload.
(* In this section, we prove a few basic lemmas about the workload. *)
Section BasicLemmas.
Context {Job: eqType}.
Variable job_arrival: Job → time.
Variable job_cost: Job → time.
(* Consider any job arrival sequence... *)
Variable arr_seq: arrival_sequence Job.
(* For simplicity, let's define some local names. *)
Let arrivals_between := jobs_arrived_between arr_seq.
(* We prove that workload can be splited into two parts. *)
Lemma workload_of_jobs_cat:
∀ t t1 t2 P,
t1 ≤ t ≤ t2 →
workload_of_jobs job_cost (arrivals_between t1 t2) P =
workload_of_jobs job_cost (arrivals_between t1 t) P
+ workload_of_jobs job_cost (arrivals_between t t2) P.
End BasicLemmas.
End Workload.