Workload Prediction of E-business Websites on Cloud Using Different Methods of ANN

Workload forecasting of cloud-based application depends on the type of application and user behavior. Measurement of workload can be done in terms of loads, data storage, service rate, processing time, etc. In this paper, author has tried to predict workload of e-business website on cloud-based environment. ANN-based approach is used by author to calculate number of cloud instances required to manage workload efficiently. Also different training method of ANN has been applied to perform comparative study. MATLAB neural network toolbox is used for simulation work. An Amazon cloud service is also used for different parameters of data collection.