K‐ear: Extracting data access periodic characteristics for energy‐aware data clustering and storing in cloud storage systems-Reference-Cited by-同舟云学术

K‐ear: Extracting data access periodic characteristics for energy‐aware data clustering and storing in cloud storage systems

Published:2020-11-30 Issue:9 Volume:33 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

You Xindong¹^ORCID,Sun Tian¹,Sun Dawei²^ORCID,Liu Xunyun³,Lv Xueqiang¹,Buyya Rajkumar⁴^ORCID

Affiliation:

1. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research Beijing Information Science and Technology University Beijing China

2. School of Information Engineering China University of Geosciences Beijing China

3. Artificial Intelligence Research Center National Innovation Institute of Defense Technology Beijing China

4. Cloud Computing and Distributed Systems (CLOUDS) Lab, School of Computing and Information Systems The University of Melbourne Melbourne Victoria Australia

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.6096

Reference42 articles.

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4. Deep learning model for home automation and energy reduction in a smart home environment platform

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