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Advances, Systems and Applications

Table 1 Workload prediction techniques

From: Proactive dynamic virtual-machine consolidation for energy conservation in cloud data centres

 

Techniques

References

Parameter

Clustering

User behavior

Window size

VM

PM

Statistical

ARIMA

[31, 127]

√

   

Fixed

[57]

 

√

  

Fixed

GFM

[94]

 

√

  

Fixed

HMM

[101]

√

 

co-clustering

 

Fixed

Bays Model

[54]

 

√

 

√

Owin=1/2 Pwin

Multi-Way Data Analysis

[99]

√

 

FCM

√

Fixed

Hybrid

AR Model, ESM, WNN, DWNN

[35]

 

√

  

Owin=2 Pwin

ECNN and LR

[85]

 

√

  

Fixed

Ensemble Model based FNN

[39]

 

√

FCM/subtractive

 

Fixed

Static and adaptive Winner Filter

[44]

√

 

k-means

 

Fixed/overlapped

ML

SVM, NN, and LR

[7]

 

√

  

Fixed

GA to optimize Elman NN

[179]

 

√

Kernal FCM

 

Fixed/overlapped

NN and Fuzzy expert

[144]

√

   

Fixed

ELM

[89]

√

 

k-mean

√

Fixed/overlapped

Multivariate ELM

[90]

√

 

FCM

√

Fixed