Advanced Mathematics and Numerical Modeling of IoT

0.0

2.0

4.0

6.0

43,200 86,400 129,600 172,800 216,000 259,200

Time (s)

Task size

m1.small

m1.large

m1.xlarge

c1.xlarge c1.medium

m2.xlarge

m2.2xlarge

m2.4xlarge

To t a lT

×10^4

(a) Total execution time

0

2

4

6

8

0

5

10

15

25

20

Costs ($)

43,200 86,400 129,600 172,800 216,000 259,200

Task size

m1.small

m1.large

m1.xlarge

c1.xlarge c1.medium

m2.xlarge

m2.2xlarge

m2.4xlarge

To t a lC

Costs ($): Total

C

(b) Costs

0.0

2.0

4.0

Time (s)

43,200 86,400 129,600 172,800 216,000 259,200

Task size

m1.small

m1.large

m1.xlarge

c1.medium

c1.xlarge

m2.xlarge

m2.2xlarge

m2.4xlarge

×10^4

(c) Failure time

0

1

2

3

4

5

Time (s)

43,200 86,400 129,600 172,800 216,000259,200

Task size

m1.small

m1.large

m1.xlarge

c1.medium

c1.xlarge

m2.xlarge

m2.2xlarge

m2.4xlarge

×10^3

(d) Rollback time

Figure 6: Simulation result in task distribution.

the total costs after applying our scheme decreased by an
average of $0.37 when compared to the cost before applying
it. There are two facts deduced from these results. One is the
increase of failure time. The other is the improvement of total
execution time through an efficient task distribution. And the
task execution loss was reduced when the out-of-bid situation
occurred. In addition, we compare experiments to consider
the execution time and costs.

Figure 8shows the combined performance metric and the
product of the total task execution time and cost. According
to the task time interval, there is a little difference between the
basic and the applying schemes, compared to each instance.
In the figure, the basic scheme denotes the workflow product
that applies only task distribution without considering a task
processing rate. The applying scheme denotes the workflow
product considering the task processing rate. The product
of the basic scheme achieves performance improvements

in the average combined metric of 87.71% over the average

productinstanceineachtasktimeinterval.Theapplying

scheme achieves performance improvements in the average

combined metric of 12.76%, compared to the basic scheme.

5. Conclusion

In this paper, we proposed a workflow scheduling tech-

niqueconsideringtaskprocessingrateinunreliablecloud

computing environments. The workflow scheduling scheme

recalculates the task size based on task processing rate within

therecalculatedpoint.Inaddition,ourpreviouslyproposed

checkpoint scheme takes a checkpointing based on two kinds

of thresholds: price and time. Our scheme reduces a failure

timeandanabsolutetimethroughthecheckpointscheme.

The rollback time of our scheme can be less than that of