Integrating clustering and regression for workload estimation in the cloud-Reference-Cited by-同舟云学术

Integrating clustering and regression for workload estimation in the cloud

Published:2020-07-20 Issue:23 Volume:32 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Yu Yongjia¹^ORCID,Jindal Vasu²,Yen I‐Ling²,Bastani Farokh²,Xu Jie³,Garraghan Peter⁴

Affiliation:

1. Changzhou College of Information Technology Changzhou China

2. Department of Computer Science University of Texas at Dallas Richardson Texas USA

3. School of Computing University of Leeds Leeds UK

4. School of Computing and Communications Lancaster University Lancaster UK

Funder

Scientific Research Project of Changzhou College of Information Technology

The Excellent Teaching Team of Qinglan Project in Jiangsu Universities 2017

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.5931

Reference32 articles.

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2. YeY XiaoL YenIL BastaniFB. Leveraging service clouds for power and QoS management for mobile devices. Paper presented at: Proceedings of the IEEE CLOUD;2011:235‐242; Washington DC.

3. ShvachkoK KuangH RadiaS ChanslerR. The Hadoop distributed file system. Paper presented at: Proceedings of the ACM Symposium on Mass Storage Systems and Technologies; May2010:1‐10.

4. Cassandra

5. YeY XiaoL YenI‐L BastaniFB. Secure dependable and high performance cloud storage. Paper presented at: 29th IEEE Symposium on Reliable Distributed Systems;2010:194‐203.

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