Using Parametric Models to Represent Private Cloud Workloads-Reference-Cited by-同舟云学术

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Using Parametric Models to Represent Private Cloud Workloads

Published:2014-10 Issue:4 Volume:7 Page:714-725
ISSN:1939-1374
Container-title:IEEE Transactions on Services Computing
language:
Short-container-title:IEEE Trans. Serv. Comput.

Author:

Wolski Richard,Brevik John

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Information Systems and Management,Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Link

http://xplorestaging.ieee.org/ielx7/4629386/6983668/06642026.pdf?arnumber=6642026

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Learning-driven hybrid scaling for multi-type services in cloud;Journal of Parallel and Distributed Computing;2024-07

2. Utilizing HAPS Deployed Data Centers in Offloading Cloud Workloads;2021 International Conference on Computational Science and Computational Intelligence (CSCI);2021-12

3. Multivariate Time Series Synthesis Using Generative Adversarial Networks;Proceedings of the ACM/SPEC International Conference on Performance Engineering;2021-04-09

4. Online Algorithms for the Interval Scheduling Problem in the Cloud: Affinity Pair Threshold based Approaches;IEEE Transactions on Sustainable Computing;2021

5. A Reinforcement Learning Approach to Price Cloud Resources With Provable Convergence Guarantees;IEEE Transactions on Neural Networks and Learning Systems;2021

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