On accurate prediction of cloud workloads with adaptive pattern mining
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-022-04647-5.pdf
Reference44 articles.
1. Chen Z, Hu J, Min G, Zomaya AY, El-Ghazawi T (2019) Towards accurate prediction for high-dimensional and highly-variable cloud workloads with deep learning. IEEE Transact Parallel Distributed Syst 31(4):923–934
2. Di S, Kondo D, Cirne W (2014) Google hostload prediction based on bayesian model with optimized feature combination. J Parallel Distrib Comput 74(1):1820–1832
3. Yang Q, Zhou Y, Yu Y, Yuan J, Xing X, Du S (2015) Multi-step-ahead host load prediction using autoencoder and echo state networks in cloud computing. J Supercomput 71(8):3037–3053. https://doi.org/10.1007/s11227-015-1426-8
4. Zhang W, Duan P, Yang LT, Xia F, Li Z, Lu Q, Gong W, Yang S (2017) Resource requests prediction in the cloud computing environment with a deep belief network. Software: Practice and Experience 47(3), 473–488 https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2426
5. Tang X, Liao X, Zheng J, Yang X (2018) Energy efficient job scheduling with workload prediction on cloud data center. Clust Comput 21(3):1581–1593. https://doi.org/10.1007/s10586-018-2154-7
Cited by 8 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. Application-Oriented Cloud Workload Prediction: A Survey and New Perspectives;Tsinghua Science and Technology;2025-02
2. HMM-CPM: a cloud instance resource prediction method tracing the workload trends via hidden Markov model;Cluster Computing;2024-06-06
3. ETSA-LP: Ensemble Time-Series Approach for Load Prediction in Cloud;Computing and Informatics;2024
4. Efficient Auto‐scaling for Host Load Prediction through VM migration in Cloud;Concurrency and Computation: Practice and Experience;2023-10-06
5. An efficient proactive VM consolidation technique with improved LSTM network in a cloud environment;Computing;2023-08-20
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3