Hybrid Metaheuristic Approach for Scheduling of Aperiodic OS Tasks - Complex System Modelling and Control Through Intelligent Soft Computations - page 832

k optimal noted Resp ðw h ; opt k according to the previous six
solutions calculated by the intelligent agent (Solution 1, Solution 2, Solution 3,
Solution 4, Solution 5 and Solution 6) by the following expression:

ne now, Resp ðw h Þ We de

Resp ðw h ; opt Þ
k

Resp ðw h Þ
k ; 1

Resp ðw h Þ
k ; 2

Resp ðw h Þ
k ; 3

Resp ðw h Þ
k ; 4

Resp ðw h Þ
k ; 5

¼ min ð ; ; ; ; ; and

Resp ðw h Þ
k

Þð the minimum of the six values Þ:

; 6

So, the calculation of Resp ðw h ; opt k allows us to obtain and to calculate the min-
imizations of response times values and to get the optimum of these values.

Running Example

In our running example, the agent proposes after the arrival of new sporadic tasks
r C , n ð 0 Þ n ðw 1 Þ ¼ fs A ; s B ; r C ; r F and r G to be added to

that evolves into

r D ; r E ; r F ; r G and r H g six solutions in order to re-obtain the feasibility of the

system.

The General EDF-based Scheduling Strategy

When dealing with the deadline tolerance factor mi, i , each task has to be computed
with respect to the deadline tolerance factor mi. i .
Algorithm GUARANTEE( n ðw h Þ ; r ðw h Þ )

a

begin
t ¼ get current time ðÞ;

R ðw h Þ
0

¼ 0 ;

d ðw h Þ
0

t;
Insert r ðw h a in the ordered task list;
n ðw h Þ ¼ n ðw h Þ [ r ðw h Þ

¼

;

a

r ðw h Þ n ðw h Þ ; k = position of in the task set

a

r ðw h Þ
i

for each task such that i ≥ kdo

{
R ðw h Þ
i

R ðw h Þ d ðw h Þ

i

d ðw h Þ c ðw h Þ

i

¼

i 1 þð i 1 Þ

;

if (R ðw h Þ
i

≥ 0) then

{
return ( “ Guaranteed ” );}
}
else