From HRT-HOOD to ADA95 [email protected] Real-Time Systems Lecture 5 Copyright, 2001 © Adam Czajka

From HRT-HOOD From HRT-HOOD to ADA95 to ADA95

[email protected]

Real-Time SystemsReal-Time Systems

Lecture 5Lecture 5

Copyright, 2001 © Adam Czajka


Contents

Introduction

HRT-HOOD objects

ADA95 mapping

Dynamic scheduling

Summary


Introduction

HRT-HOOD object types :

Pr B u f f e r

Put

* Get

Pr B u f f e r

Put

* Get

CyclicCyclic

SporadicSporadic

ProtectedProtected

PassivePassive


Introduction

Basic definitions:

TTijij – – jjthth instance of task T instance of task Tii

ii – execution time of task T – execution time of task Tii

ii – period of the task T – period of the task Tii

ijij – start time of the instance T – start time of the instance T ijij

ijij – finish time of the instance T – finish time of the instance T ijij


Introduction

Reference points for timing constraints

ss = = 1,21,2 - - 1,11,1 ee = = 1,21,2 - - 1,11,1

s

e


HRT-HOOD objects

Cyclic objects - attributes

PeriodPeriod

DeadlineDeadline

Execution timeExecution time

PriorityPriority


HRT-HOOD objects

Cyclic objects – strong periodicity

i,j+1i,j+1 - - i,ji,j = = ii

gdzie: gdzie: i, ji, j = 1, 2, 3, ... = 1, 2, 3, ...

i,1i,1 < < ii , , i,j+1i,j+1 > > i,ji,j


HRT-HOOD objects

Cyclic objects – weak periodicity

j*j*ii i,ki,k < < i,ki,k < < ((jj+1)*+1)*ii

gdzie: gdzie: i, ki, k = 1, 2, 3, ... = 1, 2, 3, ...

jj = 0, 1, 2, 3, ... = 0, 1, 2, 3, ...


HRT-HOOD objects

= < =

Cyclic objects – relative periodicity

i,j+1i,j+1 - - i,ji,j ii

gdzie: gdzie: i, ji, j = 1, 2, 3, ... = 1, 2, 3, ...

i,1i,1 < < ii , , i,j+1i,j+1 > > i,ji,j


HRT-HOOD objects

Sporadic objects - attributes

Minimum arrival timeMinimum arrival time

DeadlineDeadline

Execution timeExecution time

PriorityPriority


HRT-HOOD objects

Sporadic objects

Min. Arrival time Min. Arrival time

Cyclic object with period


HRT-HOOD objects

Sporadic objects

Sporadic objects are transformed

to cyclic ones.

Minimum arrival time = period

(worst case)

Conclusion :


ADA95 mappingADA95 mapping

Objects Objects ADA95 Packages ADA95 Packages

Cyclic objects Cyclic objects Tasks Tasks

Protected objects Protected objects Protected objects Protected objects

Passive objects Passive objects Simple packages Simple packages

Exceptions Exceptions ADA95 Exceptions ADA95 Exceptions

Rules of the mapping :



Cyclic objects

tasktask bodybody T Tii isis

beginbegin

looploop

next_time := next_time + next_time := next_time + ii; ;

................

delaydelay untiluntil next_time; next_time;

endend looploop;;

endend;;



Protected objects

protectedprotected body Pr body Pr isis

entryentry E E11 whenwhen .... ....

beginbegin

end;end;

eentryntry E E22 whenwhen .... ....

beginbegin

end;end;

endend;;


Dynamic schedulingDynamic scheduling

Liu & Layland approach (1973):

Rate Monotonic algorithmRate Monotonic algorithm

(fixed priorities)(fixed priorities)

EDF algorithmEDF algorithm

(dynamic priorities)(dynamic priorities)



Rate Monotonic algorithm

Set the tasks’ priorities according to Set the tasks’ priorities according to

the formula:the formula:

p p ii = 1 / = 1 / ii

Each time execute the task with the Each time execute the task with the

highest priorityhighest priority




For the N tasks the utilization factor U is equal to:




For a set of N tasks with fixed priority order, the least upper bound to processor utilization is

)12( /1 NNU



Rate Monotonic algorithm – ADA95 implementation

Tasks’ priorities are set by pragmaTasks’ priorities are set by pragma

pragmapragma priority(P priority(Pii))

We have 30 normal priorities and We have 30 normal priorities and

1 interrupt_priority (the highest one)1 interrupt_priority (the highest one)



Rate Monotonic algorithm – priority inversion

Pr1

T1

T2

T3

22 22

1111

33

11

33



Rate Monotonic algorithm – priority ceiling protocol

Pr1

T1

T2

T3

11

22

33

1133



Rate Monotonic algorithm – priority inversion in ADA95

We can prevent the priority inversion by We can prevent the priority inversion by

using the following pragma:using the following pragma:

pragmapragma Locking_Policy(Ceiling_Locking) Locking_Policy(Ceiling_Locking)



EDF algorithm

– the deadline driven scheduling approach

For the given moment of time, the For the given moment of time, the

priorities are assigned to the tasks priorities are assigned to the tasks

according to their current deadlines. according to their current deadlines.

A task will have the highest priority if its A task will have the highest priority if its

current deadline is the nearest. current deadline is the nearest.



EDF algorithm

– the deadline driven scheduling approach

For a given set of N tasks, the deadline driven scheduling algorithm is feasible if and only if

N

iii

1

1)/(



Implementation steps :

Write the codeWrite the code

Calculate the objects’ Calculate the objects’

attributesattributes

Set the tasks’ prioritiesSet the tasks’ priorities

Calculate the U-factorCalculate the U-factor


SummarySummary

Introduction

HRT-HOOD objects

ADA95 mapping

Dynamic scheduling

Documents

From HRT-HOOD to ADA95 [email protected] Real-Time Systems Lecture 5 Copyright, 2001 © Adam Czajka