Welcome to the InfoSci Platform
Reference Hub5
Two-Stage Adaptive Classification Cloud Workload Prediction Based on Neural Networks

Two-Stage Adaptive Classification Cloud Workload Prediction Based on Neural Networks

Lei Li, Yilin Wang, Lianwen Jin, Xin Zhang, Huiping Qin
Copyright: © 2019 |Volume: 11 |Issue: 2 |Pages: 23
ISSN: 1938-0259|EISSN: 1938-0267|EISBN13: 9781522564911|DOI: 10.4018/IJGHPC.2019040101
Cite Article Cite Article

MLA

Li, Lei, et al. "Two-Stage Adaptive Classification Cloud Workload Prediction Based on Neural Networks." IJGHPC vol.11, no.2 2019: pp.1-23. http://doi.org/10.4018/IJGHPC.2019040101

APA

Li, L., Wang, Y., Jin, L., Zhang, X., & Qin, H. (2019). Two-Stage Adaptive Classification Cloud Workload Prediction Based on Neural Networks. International Journal of Grid and High Performance Computing (IJGHPC), 11(2), 1-23. http://doi.org/10.4018/IJGHPC.2019040101

Chicago

Li, Lei, et al. "Two-Stage Adaptive Classification Cloud Workload Prediction Based on Neural Networks," International Journal of Grid and High Performance Computing (IJGHPC) 11, no.2: 1-23. http://doi.org/10.4018/IJGHPC.2019040101

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Workload prediction is important for automatic scaling of resource management, and a high accuracy of workload prediction can reduce the cost and improve the resource utilization in the cloud. But, the task request is usually random mutation, so it is difficult to achieve more accurate prediction result for single models. Thus, to improve the prediction result, the authors proposed a novel two-stage workload prediction model based on artificial neural networks (ANNs), which is composed of one classification model and two prediction models. On the basis of the first-order gradient feature, the model can categorize the workload into two classes adaptively. Then, it can predict the workload by using the corresponding prediction neural network models according to the classification results. The experiment results demonstrate that the suggested model can achieve more accurate workload prediction compared with other models.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.