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Advances, Systems and Applications

Table 6 Algorithm parameter settings

From: A resource scheduling method for cloud data centers based on thermal management

Algorithm

UACO

ACS_VMC

EVMCACS

Number of ants:\({N}_{ant}\)

15

15

15

Number of iterations:\({N}_{c}\)

10

10

10

Critical number:\({c}_{0}\)

0.7

0.7

0.7

Local pheromone volatile factor:\(\rho\)

0.3

0.3

-

Global pheromone volatile factor:\(\sigma\)

0.4

0.4

0.4

Pheromone importance factor:\(\alpha\)

0.9

-

-

Importance factor of heuristic information:\(\beta\)

0.9

0.9

0.9

The maximum proportion of increase in pheromone concentration:\({\Delta \tau }_{max}\)

1.5

-

-

Weight of power consumption in fitness function:\(\varepsilon\)

0.5

-

-

Weight of the number of hosts closed in fitness function:\(\gamma\)

-

5

5