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Network-aware virtual machine placement using enriched butterfly optimisation algorithm in cloud computing paradigm
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DOI：10.1007/s10586-024-04389-4.png)
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Abstract
En 中文
This article presents a virtual machine placement technique aimed at minimizing power usage in heterogeneous cloud data centers. In this study, an innovative model for minimizing the power usage of a datacenter's network is provided. The Enriched Discrete Butterfly Optimization method (EDBOA) is used as a meta-heuristic method in order to achieve an effective mapping of virtual machines (VMs) onto physical machines (PMs). The Reverse Order Filling Method (ROFM) was developed as a solution repair technique to meet the requirements of the BOA. It is used to manipulate the solutions in order to identify potential candidates;
more optimum solutions. Furthermore, we constructed VM's that had both Left-Right and Top-Down communication capabilities. Additionally, PM's with limited capacities in terms of CPU, memory, and bandwidth are designed and included;
the purpose of testing. The integration of our network power model into the EDBOA algorithms facilitates the calculation of both power modules and network power consumption. A detailed comparative analysis was conducted on our suggested approaches and many other comparable methods. The evaluation findings demonstrate that the offered approaches exhibit strong per;
mance, with the BOA algorithm using the ROFM solution repair surpassing other methods in terms of power usage. The assessment findings also demonstrate the importance of network power usage.
Keywords:
Reverse order filling
Butterfly optimisation algorithm
Virtual machine placement
Network-aware
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