Future Internet Technologies and Trends. First International Conference, ICFITT 2017, Surat, India, August 31 - September 2, 2017, Proceedings

Research Article

Efficient Resource Monitoring and Prediction Techniques in an IaaS Level of Cloud Computing: Survey

Download
253 downloads
  • @INPROCEEDINGS{10.1007/978-3-319-73712-6_5,
        author={Vivek Prasad and Madhuri Bhavsar},
        title={Efficient Resource Monitoring and Prediction Techniques in an IaaS Level of Cloud Computing: Survey},
        proceedings={Future Internet Technologies and Trends. First International Conference, ICFITT 2017, Surat, India, August 31 - September 2, 2017, Proceedings},
        proceedings_a={ICFITT},
        year={2018},
        month={2},
        keywords={Cloud computing Monitoring Prediction Under provisioning Over provisioning IaaS},
        doi={10.1007/978-3-319-73712-6_5}
    }
    
  • Vivek Prasad
    Madhuri Bhavsar
    Year: 2018
    Efficient Resource Monitoring and Prediction Techniques in an IaaS Level of Cloud Computing: Survey
    ICFITT
    Springer
    DOI: 10.1007/978-3-319-73712-6_5
Vivek Prasad1,*, Madhuri Bhavsar1,*
  • 1: Nirma University
*Contact email: vivek.prasad@nirmauni.ac.in, madhuri.bhavsar@nirmauni.ac.in

Abstract

In this paper, we have discussed about the various techniques through which the cloud computing monitoring and prediction can be achieved, This paper provides the survey of the techniques related to monitoring and prediction for the efficient usages of the resources available at the IaaS level of cloud. As cloud provides the services, which are elastic, scalable or highly dynamic in nature, which binds us to make the correct usages of the resources, but in real situations the (Cloud Service Provider)CSP’s has to face the situation of under provisioning and over provisioning, where the resources are not fully utilized and being wasted, though this is the survey paper, it ends up with the proposed model where both the concepts of the Monitoring and Prediction will be combined together to give a better vision of the future resource demand in IaaS layer of Cloud Computing.