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AOMO: An AI-aided Optimizer for Microservices Orchestration

Published:19 August 2019Publication History

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References

  1. Alibaba. 2017. Alibaba Cluster Data v2017. (2017). http://bit.ly/alidata2018 Accessed on 2019-06-06.Google ScholarGoogle Scholar
  2. Carlos Guerrero and Isaac Lera, et al. 2018. Resource optimization of container orchestration: a case study in multi-cloud microservices-based applications. The Journal of Supercomputing (2018), 1--28. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Gueyoung Jung and Matti A Hiltunen, et al. 2010. Mistral: Dynamically managing power, performance, and adaptation cost in cloud infrastructures. In 2010 30th ICDCS. IEEE, 62--73. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. LightStep. 2018. Global Microservices Trends: A Survey of Development Professionals. (2018). http://bit.ly/trendsofms Accessed on 2019-04-29.Google ScholarGoogle Scholar
  5. Benedict Michael and Charanya Vinu. 2017. How we built a metering and charge-back system to incentivize higher resource utilization of twitter infrastructure. (2017). http://bit.ly/twitteryoutubems Accessed on 2019-04-29.Google ScholarGoogle Scholar
  6. Adalberto R Sampaio and Julia Rubin, et al. 2019. Improving microservice-based applications with runtime placement adaptation. Journal of Internet Services and Applications 10, 1 (2019), 4.Google ScholarGoogle ScholarCross RefCross Ref

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  1. AOMO: An AI-aided Optimizer for Microservices Orchestration

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      • Published in

        cover image ACM Conferences
        SIGCOMM Posters and Demos '19: Proceedings of the ACM SIGCOMM 2019 Conference Posters and Demos
        August 2019
        183 pages
        ISBN:9781450368865
        DOI:10.1145/3342280

        Copyright © 2019 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 19 August 2019

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        Qualifiers

        • short-paper
        • Research
        • Refereed limited

        Acceptance Rates

        SIGCOMM Posters and Demos '19 Paper Acceptance Rate62of102submissions,61%Overall Acceptance Rate554of3,547submissions,16%

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