Title :
Study on predicting for workload of cloud services using Artificial Neural Network
Author :
Sahi, Supreet Kaur ; Dhaka, V.S.
Author_Institution :
Jaipur Nat. Univ., Jaipur, India
Abstract :
In cloud computing virtual machines are kept on the cloud. Workload of cloud computing differ from one application to other. Load, network needs, bandwidth and other metrics for workload prediction depends upon different characteristics of applications. Different resources required by e-business based website can be acquired from cloud service providers. To find out the amount of cloud resources required for efficient workload management of e-business website is aim of this paper. This paper propose Artificial Neural Network based model for predicting workload of e-business website on cloud network. Simulation will be done using Matlab toolbox and data available on Amazon website will be used as sample data of model.
Keywords :
Web sites; business data processing; cloud computing; neural nets; virtual machines; Amazon Web site; Matlab toolbox; artificial neural network; cloud computing; cloud services; e-business based Web site; virtual machines; workload management; workload prediction; Artificial neural networks; Capacity planning; Cloud computing; Computational modeling; Mathematical model; Predictive models; Training; ANN (Artificial Neural Network); E-Business; IaaS; Matlab Toolbox; Simulation;
Conference_Titel :
Computing for Sustainable Global Development (INDIACom), 2015 2nd International Conference on
Conference_Location :
New Delhi
Print_ISBN :
978-9-3805-4415-1
