Future Clients' Requests Estimation for Dynamic Resource Allocation in Cloud Data Center Using CGPANN

Abstract

Cloud computing is an emerging and rapid growing field of Infrastructure as a Service (IaaS), it has to deal with resource allocation and power management issues. This paper proposes CGPANN to accurately forecast the client's requests for a very short term duration of 1 second. A forecasting accuracy as high as 99.81% has been attained that verifies the accuracy of the proposed model. The experimental results show that the model outperforms all the contemporary models proposed in past.