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Conference Papers Year : 2012

Autonomous and Energy-Aware Management of Large-Scale Cloud Infrastructures

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Abstract

With the advent of cloud computing and the need for increasing amount of computing power, cloud infrastructure providers are now facilitating the deployment of large-scale data centers. In order to efficiently manage such environments three important properties have to be fulfilled by their resource management frameworks: (1) scalability; (2) autonomy (i.e. self-organization and healing); (3) energy-awareness. However, existing open-source cloud management stacks (e.g. Eucalyptus, Nimbus, OpenNebula, OpenStack) have a high degree of centralization and limited power management support. In this context, this PhD thesis focuses on more scalable, autonomic, and energy-aware resource management frameworks for large-scale cloud infrastructures. Particularly, a novel virtual machine (VM) management system based on a self-organizing hierarchical architecture called Snooze is proposed. In order to conserve energy, Snooze automatically transitions idle servers into a low-power mode (e.g. suspend). To favor idle times the system integrates a nature-inspired VM consolidation algorithm based on the Ant Colony Optimization (ACO).
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Dates and versions

hal-00676295 , version 1 (20-07-2012)

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  • HAL Id : hal-00676295 , version 1

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Eugen Feller, Christine Morin. Autonomous and Energy-Aware Management of Large-Scale Cloud Infrastructures. PhD Forum of the 26th IEEE International Parallel & Distributed Processing Symposium (IPDPS PhD Forum), May 2012, Shanghai, China. ⟨hal-00676295⟩
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