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This question aims to investigate the objective values of the best optimization algorithm selected in RQ1 against the proposed solution from the default schedule as well as minimize the resources consumption (i.e., CPU and memory usage). The goal of this research questions is to identify if our approach can reduce such metrics by just rearranging containers in a different manner.
This question aims to investigate the objective values of the best optimization algorithm selected in RQ1 against the proposed solution from the default schedule as well as minimize the resources consumption (i.e., CPU and memory usage). The goal of this research questions is to identify if our approach can reduce such metrics by just rearranging containers in a different manner.
Results :
Scenario 1
==> Our scheduler is able to balance the resources consumption and the load among the nodes by taking into account the resources
consumed by each container in the cluster, as well as the remaining memory and CPU for each node.
Scenario 2
==> Our scheduler is able to shift containers to active nodes in the event of a Fail Operational or Software Upgrade in certain nodes, while preserving the priorities and placement constraints, as well as the resources limits of the activated nodes in the cluster. After it has returned to normal The scheduler returns the ECU to the cluster.
Scenario 3
==> Once in a LPM mode, our scheduler is able to manage the containers distribution while respecting the nodes power limits and the containers placement constraints.
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