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A novel approach to workload prediction using...
Journal article

A novel approach to workload prediction using attention-based LSTM encoder-decoder network in cloud environment

Abstract

Server workload in the form of cloud-end clusters is a key factor in server maintenance and task scheduling. How to balance and optimize hardware resources and computation resources should thus receive more attention. However, we have observed that the disordered execution of running application and batching seriously cuts down the efficiency of the server. To improve the workload prediction accuracy, this paper proposes an approach using the …

Authors

Zhu Y; Zhang W; Chen Y; Gao H

Journal

EURASIP Journal on Wireless Communications and Networking, Vol. 2019, No. 1,

Publisher

Springer Nature

Publication Date

December 2019

DOI

10.1186/s13638-019-1605-z

ISSN

1687-1472