Network-aware virtual machine placement using enriched butterfly optimisation algorithm in cloud computing paradigm

FOS: Computer and information sciences Artificial intelligence Computer Networks and Communications Heuristic 02 engineering and technology Cloud Computing and Big Data Technologies Quantum mechanics Network Virtualization Virtualization 0202 electrical engineering, electronic engineering, information engineering Edge Computing Cloud computing Network Function Virtualization Internet of Things and Edge Computing Physics Software-Defined Networking and Network Virtualization Power (physics) Computer science Virtual machine Distributed computing Virtual Network Embedding Algorithm Operating system Power consumption Computer Science Physical Sciences Information Systems
DOI: 10.1007/s10586-024-04389-4 Publication Date: 2024-04-12T19:01:36Z
ABSTRACT
Abstract 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 the of datacenter’s network is provided. The Enriched Discrete Butterfly Optimization method (EDBOA) used as meta-heuristic order to achieve effective mapping machines (VMs) onto physical (PMs). Reverse Order Filling Method (ROFM) was developed solution repair meet requirements BOA. It manipulate solutions 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 terms CPU, memory, bandwidth are designed included purpose testing. integration our into EDBOA algorithms facilitates calculation modules consumption. A detailed comparative analysis conducted on suggested approaches many other comparable methods. evaluation findings demonstrate offered exhibit strong performance, BOA algorithm using ROFM surpassing methods usage. assessment also importance
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