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Require Export prosa.analysis.abstract.search_space.Require Import prosa.analysis.facts.priority.fifo.Require Import prosa.analysis.definitions.sbf.pred.(** * The Abstract Search Space is a Subset of the FIFO Search Space *)(** A response-time analysis usually involves solving the response-time equation for various relative arrival times (w.r.t. the beginning of the corresponding busy interval) of a job under analysis. To reduce the time complexity of the analysis, the state of the art uses the notion of a search space. Intuitively, this corresponds to all "interesting" arrival offsets that the job under analysis might have with regard to the beginning of its busy window. In this file, we prove that the search space derived from the aRTA theorem is a subset of the search space for the FIFO scheduling policy with restricted supply. In other words, by solving the response-time equation for points in the FIFO search space, one also checks all points in the aRTA search space, which makes FIFO compatible with aRTA w.r.t. the search space. *)SectionSearchSpaceSubset.(** Consider a restricted-supply uniprocessor model where the minimum amount of supply is defined via a monotone unit-supply-bound function [SBF]. *)Context {SBF : SupplyBoundFunction}.(** Consider any type of tasks. *)Context {Task : TaskType}.Context `{TaskCost Task}.(** Consider an arbitrary task set [ts]. *)Variablets : seq Task.(** 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}.HypothesisH_valid_arrival_curve :
valid_taskset_arrival_curve ts max_arrivals.(** For brevity, let's denote the request-bound function of a task as [rbf]. *)Letrbftsk := task_request_bound_function tsk.(** Let [L] be an arbitrary positive constant. Typically, [L] denotes an upper bound on the length of a busy interval of a job of [tsk]. In this file, however, [L] can be any positive constant. *)VariableL : duration.HypothesisH_L_positive : 0 < L.(** In the case of [FIFO], the concrete search space is the set of offsets less than [L] such that there exists a task [tsk] in [ts] such that [rbf tsk (A) ≠ rbf tsk (A + ε)]. *)Definitionis_in_search_space (A : duration) :=
letrbf_makes_a_steptsk := rbf tsk A != rbf tsk (A + ε) in
(A < L) && has rbf_makes_a_step ts.(** Let [tsk] be any task in [ts] that is to be analyzed. *)Variabletsk : Task.HypothesisH_tsk_in_ts : tsk \in ts.(** To rule out pathological cases with the search space, we assume that the task cost is positive and the arrival curve is non-pathological. *)HypothesisH_task_cost_pos : 0 < task_cost tsk.HypothesisH_arrival_curve_pos : 0 < max_arrivals tsk ε.(** For brevity, let us introduce a shorthand for an IBF (used by aRTA). The abstract search space is derived via IBF. *)Local DefinitionIBF (AF : duration) :=
(F - SBF F) + (total_request_bound_function ts (A + ε) - task_cost tsk).(** Then, abstract RTA's standard search space is a subset of the computation-oriented version defined above. *)