Open AccessPrediction of CPU Utilization in Cloud Environment during Seasonal Trend
Author(s) -
Smitha Krishnan,
Dr B.G Prasanthi
Publication year - 2021
Publication title -
international journal on recent and innovation trends in computing and communication
Language(s) - English
Resource type - Journals
ISSN - 2321-8169
DOI - 10.17762/ijritcc.v9i12.5493
Subject(s) - cloud computing , computer science , workload , quality of service , scalability , service (business) , service level , distributed computing , database , operating system , computer network , statistics , economy , mathematics , economics
Today, the most recent paradigm to emerge is that of Cloud computing, which promises reliable services delivered to the end-user through next-generation data centres which are built on virtualized compute and storage technologies Consumer will be able to access desired service from a “Cloud” anytime anywhere in the world on the bases of demand. Computing services need to be highly reliable, scalable, easy accessible and autonomic to support ever-present access, dynamic discovery and computability, consumers indicate the required service level through Quality of Service (QoS) parameters, according to Service Level Agreements (SLAs) A suitable mdel for the prediction is being developed. Here Genetic Algorithm is chosen in combination with stastical model to do the workload prediction .It is expected to give better result by producing less error rate and more accuracy of prediction compared to the previous algorithm.