Evaluating performance variations cross cloud data centres using multiview comparative workload traces analysis-Reference-Cited by-同舟云学术

Evaluating performance variations cross cloud data centres using multiview comparative workload traces analysis

Published:2022-06-11 Issue:1 Volume:34 Page:1582-1608
ISSN:0954-0091
Container-title:Connection Science
language:en
Short-container-title:Connection Science

Author:

Ruan Li¹²³⁴,Xu Xiangrong²,Xiao Limin¹²,Ren Lei⁵,Min-Allah Nasro⁶,Xue Yunzhi⁷

Affiliation:

1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, People's Republic of China

2. School of Computer Science and Engineering, Beihang University, Beijing, People's Republic of China

3. Yunnan Key Lab-oratory of Blockchain Application Technology, Yunnan, People's Republic of China

4. Standard Laboratory for Traffic Crash Investigation and Reconstruction of ICV, Beijing, People's Republic of China

5. School of Automation Science and Electrical Engineering, Beihang University, Beijing, People's Republic of China

6. College of Computer Science and Information Technology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia

7. Institute of Software, Chinese Academy of Science, Beijing, People's Republic of China

Funder

NSFC

the State Key Laboratory of Software Development Environment

The Shandong Provincial Key Research and Development Program

The National Key R&D Program of China

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Human-Computer Interaction,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/09540091.2021.2015289

Reference39 articles.

1. Alibaba (2018). Alibaba cluster-data. Retrieved November 5, 2021, from https://github.com/alibaba/clusterdata/.

2. Investigation and Analysis of Google Cluster Usage Traces: Facts and Real-Time Issues

3. Amvrosiadis, G., Park, J. W., Ganger, G. R., Gibson, G. A., Baseman, E. & DeBardeleben, N. (2018). On the diversity of cluster workloads and its impact on research results. In 2018 {USENIX} Annual Technical Conference ({USENIX};{ATC} 18) (pp. 533–546). USENIX Association.

4. A Big Data analyzer for large trace logs

Cited by 4 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. ERAM-EE: Efficient resource allocation and management strategies with energy efficiency under fog–internet of things environments;Connection Science;2024-05-06

2. PArtNNer: Platform-Agnostic Adaptive Edge-Cloud DNN Partitioning for Minimizing End-to-End Latency;ACM Transactions on Embedded Computing Systems;2024-01-10

3. Arithmetic Study about Efficiency in Network Topologies for Data Centers;Network;2023-06-26

4. An Ensemble Learning Approach For Task Failure Prediction In Cloud Data Centers;E3S Web of Conferences;2023