A new efficient approach for extracting the closed episodes for workload prediction in cloud-Reference-Cited by-同舟云学术

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A new efficient approach for extracting the closed episodes for workload prediction in cloud

Published:2019-06-13 Issue:1 Volume:102 Page:141-200
ISSN:0010-485X
Container-title:Computing
language:en
Short-container-title:Computing

Author:

Amiri Maryam,Mohammad-Khanli Leyli,Mirandola Raffaela

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Numerical Analysis,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00607-019-00734-3.pdf

Reference49 articles.

1. Petcu D, Vzquez-Poletti JL (2012) European research activities in cloud computing. Cambridge Scholars Publishing, Cambridge

2. Amiri M, Mohammad-Khanli L, Mirandola R (2018) An online learning model based on episode mining for workload prediction in cloud. Future Gener Comput Syst 87:83

3. Amiri M, Mohammad-Khanli L (2017) Survey on prediction models of applications for resources provisioning in cloud. J Netw Comput Appl 82:93–113

4. Jiang Y, Perng C-S, Li T, Chang RN (2013) Cloud analytics for capacity planning and instant VM provisioning. IEEE Trans Netw Serv Manag 10(3):312–325

5. Cetinski K, Juric MB (2015) AME-WPC: advanced model for efficient workload prediction in the cloud. J Netw Comput Appl 55:191–201

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