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Automatic Resource Management in Geo-Distributed Multi-Cluster Environments

Mulugeta Ayalew Tamiru 1, 2
2 MYRIADS - Design and Implementation of Autonomous Distributed Systems
Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
Abstract : Geo-distributed computing environments such as hybrid cloud, multi-cloud and Fog Computing need to be managed autonomously at large scales to improve resource utilization, maximize performance, and save costs. However, resource management in these geo-distributed computing environments is difficult due to wide geographical distributions, poor network conditions, heterogeneity of resources, and limited capacity. In this thesis, we address some of the resource management challenges using container technology. First, we present an experimental analysis of autoscaling in Kubernetes clusters at the container and Virtual Machine levels. Second, we propose a proportional controller to dynamically improve the stability of geo-distributed deployments at run-time in Kubernetes Federations. Finally, we develop a container orchestration framework for geo-distributed environments that offers policy-rich placement, autoscaling, bursting, network routing, and dynamic resource provisioning capabilities.
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Contributor : Guillaume Pierre Connect in order to contact the contributor
Submitted on : Wednesday, September 22, 2021 - 2:43:13 PM
Last modification on : Tuesday, October 19, 2021 - 11:04:35 AM


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  • HAL Id : tel-03351598, version 1


Mulugeta Ayalew Tamiru. Automatic Resource Management in Geo-Distributed Multi-Cluster Environments. Operating Systems [cs.OS]. Université de Rennes 1, 2021. English. ⟨tel-03351598⟩



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