Electron: Towards Efficient Resource Management on Heterogeneous Clusters with Apache Mesos

DelValle, Renan; Kaushik, Pradyumna; Jain, Abhishek; Hartog, Jessica; Govindaraju, Madhusudhan

doi:10.1109/cloud.2017.41

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Selection Of Hacs For the Survey1

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Cited by 4 publications

(2 citation statements)

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“…Apache Mesos [152] focus on specific IT solutions (HPC) DxEnterprise [153] lack of EA support; insufficient information available to evaluate the solution properly everRun [154] lack of EA support; insufficient information available to evaluate the solution properly HA-OSCAR [155] no longer active Kimberlite [55] no longer active Linux FailSafe [55] no longer active…”

Section: Selection Of Hacs For the Surveymentioning

confidence: 99%

High-availability clusters: A taxonomy, survey, and future directions

Somasekaram

Călinescu

Buyya

2022

Journal of Systems and Software

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Section: Selection Of Hacs For the Surveymentioning

confidence: 99%

High-availability clusters: A taxonomy, survey, and future directions

Somasekaram

Călinescu

Buyya

2022

Journal of Systems and Software

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“…An interesting contribution exploiting Mesos is in DelValle et al (2017). It proposes a framework, Electron, which aims to reduce power peaks and energy consumption for the slave nodes in a heterogeneous cluster.…”

Section: Related Workmentioning

confidence: 99%

Scheduling communication-intensive applications on Mesos

Stefano

Morana³

2020

IJGUC

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In recent years, the widespread use of container technologies has significantly altered the interactions between cloud service providers and their customers when developing and offering services. The shift away from Virtual Private Server scenarios in Infrastructure-as-a-Service environments requires drastic changes to the deployment strategies adopted by service providers. This also opens many questions to what information must be supplied by customers and how to improve the performance of user applications, especially in the case of communication-intensive applications. In this work, the authors propose the adoption of a new framework for Mesos clusters that aims to improve the deployment strategies of communication intensive applications. Coope4M is based on the partitioning of the user application graph via the Isolation Index parameter obtained through user-knowledge on the degree of the communication between its components.

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