An energy-efficient task and virtual machine placement in virtualised cloud server using FY-SFLA and RMMS-DLVQ Online publication date: Thu, 23-Nov-2023
by E.P. Sudhakar; M. Saravanan
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 29, No. 2, 2023
Abstract: Creating infrastructures, virtual servers, computing resources, along with devices is termed virtualisation. In this methodology, to augment resource usage along with to mitigate the total power consumption, mapping of a group of virtual machine (VM) onto a set of physical machines (PM) is performed in a data centre (DC). Nevertheless, a crucial challenge is presented by the VM allocation together with the higher energy consumption (EC) of cloud data centres (CDC). Thus, to alleviate the resource wastage along with to mitigate the DCs' EC, an effectual Fisher Yates-Shuffled frog leaping algorithm (FY-SFLA) is proposed here: 1) task feature extraction; 2) resource information extraction; 3) task separation by utilising cosine distance - K means algorithm (CD-KMA); 4) task placement in VM by employing the FY-SFLA task; 5) VM status identification by deploying random mutation monkey search deep learning vector quantisation (RMMS - DLVQ) are '5' phases comprised in the proposed methodology.
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