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Large Scale and Big Data
book

Large Scale and Big Data

by Sherif Sakr, Mohamed Gaber
June 2014
Intermediate to advanced content levelIntermediate to advanced
636 pages
23h 13m
English
Auerbach Publications
Content preview from Large Scale and Big Data
567Performance Analysis for Large IaaS Clouds
Probability (P
h
) that a hot pool can accept a job for provisioning is given by
PB
hh
n
h
=−1( )
(18.27)
Observe that P
h
is used as an input parameter in the RPDE submodel (Figure 18.2).
18.3.4 sharPe CoDe For hot Pm submoDel
We present the SHARPE code for hot PM submodel below.
format 8
bind
* Dummy value of P_block
P_block 0.01
P_not_blocked 1-P_block
lambda 1000
beta_h 12
m 4
Lh 2
mu 1
n_h 10
epsilon_zero 0.000001
end
* Function to compute effective arrival rate for each hot PM
func lambda_h(i)
if (i==0)
0
else
lambda*P_not_blocked/i
end
end
* Markov model to describe VM provisioning model for hot PM
markov hot(num_hot)
loop i,0,m-1
0_0_$(i) 0_1_$(i) lambda_h(num_hot)
end
loop j,0,m-1
loop i,0,Lh-1
$(i)_1_$(j) $(i+1)_1_$(j) ...
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Publisher Resources

ISBN: 9781466581500