Skip to main content

Advances, Systems and Applications

Table 18 The genetic algorithm behavior in an environment with the growing workload

From: Using genetic algorithms to find optimal solution in a search space for a cloud predictive cost-driven decision maker

Iteration no.

CR

CSLA

No. of rented VMs

No. of SLA breaches

Optimal Configuration

1

1

1

127

1

< 95, 53, 0, 3, 0, 0>

2

1

5

127

1

< 95, 53, 0, 3, 0, 0>

3

1

10

153

0

< 80, 29, 0, 4, 0, 4>

4

1

15

153

0

< 80, 29, 0, 4, 0, 4>

5

1

20

153

0

< 80, 29, 0, 4, 0, 4>

6

1

25

153

0

< 80, 29, 0, 4, 0, 4>

7

1

30

153

0

< 80, 29, 0, 4, 0, 4>

8

5

1

96

80

< 96, 70, 4, 0, 3, 2>

9

10

1

96

80

< 96, 70, 4, 0, 3, 2>

10

15

1

96

80

< 96, 70, 4, 0, 3, 2>

11

20

1

90

91

< 97, 65, 4, 0, 4, 0>

12

25

1

88

94

< 99, 69, 4, 0, 4, 0>

13

30

1

88

94

< 99, 69, 4, 0, 4, 0>