A STUDY ON HOST MACHINE OVERLOAD DETECTION ALGORITHM IN CLOUD DATA CENTER

Abstract

A critical step in the motion of virtual machine consolidation (VMs)process is host-overloading detection. A particularly intriguing method of avoiding host overload is to use machine learning to forecast future host demand. Host overflow detection, which attempts to foretell whether or not a physical server will become overloaded by VMs, is a crucial stage when consolidating VMs. Major cloud management difficulties in relation to clouds computing include energy utilisation and service level agreements (SLAs). The utilisation inside cloud computing data centres is rapidly growing to meet the large growth in demand for high-performance computing (HPC), storage, and networking resources for commercial and academic purposes. In this research, we attempt to study the performance of the detection of host overload algorithm in cloud datacenters.