Mobile cloud calculation adaptive virtual machine scheduling method based on improved particle swarm
A technology for improving particle swarm and scheduling methods, applied in the field of cloud computing and machine learning, can solve problems such as incomplete consideration and non-consideration, and achieve the effects of reducing energy consumption, increasing convergence speed, and improving solution speed
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[0115] The experimental simulation is carried out by using the cloud computing simulation tool CloudSim. A heterogeneous virtualized data center containing 400 heterogeneous servers is simulated. In order to reflect the heterogeneity of the virtualized data center, two types of servers are selected, which have different configurations and energy consumption characteristics. The parameters and characteristics of the servers are shown in the table 2. The power consumption (watts) of the selected servers at different load levels is shown in Table 3. The parameter settings of the comparative simulation experiment are shown in Table 4. In Table 4 ω 1 , ω 2 , ω 3 , ω 4 They are CPU energy consumption weight, memory energy consumption weight, hard disk energy consumption weight, and network bandwidth energy consumption weight respectively. Table 5 shows the virtual machine instance of this embodiment.
[0116] Table 2 Server parameter characteristics
[0117]
[0118] Tabl...
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