Performance Analysis of Machine Learning Centered Workload Prediction Models for Cloud-Reference-Cited by-同舟云学术

Performance Analysis of Machine Learning Centered Workload Prediction Models for Cloud

Published:2023-04 Issue:4 Volume:34 Page:1313-1330
ISSN:1045-9219
Container-title:IEEE Transactions on Parallel and Distributed Systems
language:
Short-container-title:IEEE Trans. Parallel Distrib. Syst.

Author:

Saxena Deepika¹^ORCID,Kumar Jitendra²,Singh Ashutosh Kumar³^ORCID,Schmid Stefan⁴^ORCID

Affiliation:

1. Department of Computer Science, Goethe University Frankfurt, Frankfurt, Germany

2. Department of Computer Applications, NIT Tiruchirappalli, Tamilnadu, India

3. Department of Computer Applications, NIT Kurukshetra, Thanesar, HR, India

4. TU Berlin, Berlin, Germany

Funder

National Institute of Technology, Kurukshetra

Goethe University, Frankfurt

Austrian Science Fund

Deutsche Forschungsgemeinschaft

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/71/10043602/10029931.pdf?arnumber=10029931

Reference64 articles.

1. Quantum Machine Learning Driven Malicious User Prediction for Cloud Network Communications

2. Prediction of cloud data center networks loads using stochastic and neural models

3. Workload forecasting and resource management models based on machine learning for cloud computing environments;saxena,2021

4. A Quantum Approach Towards the Adaptive Prediction of Cloud Workloads

5. Communication cost aware resource efficient load balancing (CARE-LB) framework for cloud datacenter;saxena;Recent Advances in Computing and Communications,2020

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