{'fraction_non_alphanumeric': 0.017313432835820895, 'fraction_numerical': 0.0011940298507462687, 'mean_word_length': 5.868852459016393, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Vpm tokens: virtual machine-aware power budgeting in datacenters

Power consumption and cooling overheads are becoming increasingly significant for large scale machines, affecting overall costs and the ability to extend resource capacities and performance capabilities. To help mitigate these issues, active power management technologies are being deployed aggressively, including power budgeting, which enables improved power provisioning and can address critical periods when power delivery or cooling capabilities are temporarily reduced. Given the use of virtualization to encapsulate application components into virtual machines (VMs), however, such power management capabilities must address the interplay between budgeting physical resources and the performance of the virtual machines used to run these applications. This paper proposes a set of cluster- and datacenter-level management components and abstractions for use by power budgeting policies. The key idea is to manage power from a VM-centric point of view, where the goal is to be aware of global utility tradeoffs between different virtual machines (and their applications) when maintaining power constraints for the physical hardware on which they run. Our approach to VM-aware power budgeting uses multiple distributed managers integrated into the VirtualPower Management (VPM) framework whose actions are coordinated via a new abstraction, termed VPM tokens. An implementation with the Xen hypervisor illustrates technical benefits of VPM tokens that include up to 43% improvements in global utility, highlighting the ability to dynamically improve cluster performance while still meeting power budgets.