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Automatic Generation of Workload Profiles Using Unsupervised Learning Pipelines

  • Published:2018-03 Issue:1 Volume:15 Page:142-155
  • ISSN:1932-4537
  • Container-title:IEEE Transactions on Network and Service Management
  • language:
  • Short-container-title:IEEE Trans. Netw. Serv. Manage.

Author:

Prats David Buchaca,Berral Josep Lluis,Carrera David

Funder

European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme

Ministry of Economy of Spain

Generalitat de Catalunya

ICREA Academia program

BSC-CNS Severo Ochoa program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Cited by 12 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. Resource Demand Profiling of Monolithic Workflows;Companion of the 15th ACM/SPEC International Conference on Performance Engineering;2024-05-07

2. A Greener Meta-Heuristics Scheduling Algorithm With Energized Optimization Dynamics by Deeper Intelligence Fusion;IEEE Access;2021

3. Proactive Container Auto-scaling for Cloud Native Machine Learning Services;2020 IEEE 13th International Conference on Cloud Computing (CLOUD);2020-10

4. Improving maritime traffic emission estimations on missing data with CRBMs;Engineering Applications of Artificial Intelligence;2020-09

5. Sequence-to-sequence models for workload interference prediction on batch processing datacenters;Future Generation Computer Systems;2020-09
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