Advances, Systems and Applications
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 |