Titlebook: Energy Efficiency in Large Scale Distributed Systems; COST IC0804 European Jean-Marc Pierson,Georges Da Costa,Lars Dittmann Conference proc

Communal

corpus-callosum

Snooze: An Autonomic and Energy-Efficient Management System for Private Clouds to save energy. Last but not least, it integrates a generic scheduler which allows to implement any VM placement algorithm. This demo will expose the Snooze’s main properties (scalability, energy-efficiency, autonomy, and fault-tolerance) through its graphical interface.

6Applepolish

Energy Efficiency in Secure and Dynamic Cloud Storageof the update operations. Moreover, we developed an algorithm to carry out multiple challenges at once. We have tested our algorithm, and the results show time and energy efficiencies of ., ., . and . for file sizes 4MB, 40MB, 400MB, and 4GB respectively.

Nebulizer

Solving Some Mysteries in Power Monitoring of Servers: Take Care of Your Wattmeters!fferent measured lines, the internal wattmeters allow an improved visualization of some power fluctuations. However, a high sampling rate is not always necessary to understand the evolution of the power consumption during the execution of a benchmark.

LUDE

EnergyBox: A Trace-Driven Tool for Data Transmission Energy Consumption Studiesheld devices. EnergyBox enables efficient energy consumption studies using real data, which complements the device-dependent laborious physical power measurements. Using real application transmission traces, we have validated EnergyBox showing an accuracy range of 94–99% for 3G and 93–99% for WiFi c

watertight,

The interest in . has grown steadily over recte the activities of a group of Virtual Machine managed by a Virtualized Data Center Manager and observe the resulting performances. This extensible framework allows to describe, via a scripting language, a scenario of system resources use in Virtual Machines, execute it on a Infrastructure as a Ser

PANG

Galactogogue

Energy Characterization of Data Mining Algorithms on Mobile Devicesthms running on mobile devices. Specifically, we consider algorithms for association rule mining, clustering, and decision tree induction. Our study reveals that, although data mining algorithms are compute- and memory-intensive, by appropriate tuning of a few parameters associated to data (e.g., da

Incisor

A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environmentse three widespread virtualization frameworks, namely Xen, KVM, and VMware ESXi and compare them with a . environment running in native mode. The conducted experiments were performed on top of benchmarking tools that reflect an HPC usage, i.e. HPCC, IOZone and Bonnie++. To abstract from the specific

奇思怪想

A Three Step Blind Approach for Improving HPC Systems’ Energy Performance into phase detection, phase characterization, and phase identification and system reconfiguration. And it is blind in the sense that it does not require any knowledge from users. It relies upon reconfigurable capabilities offered by the majority of HPC subsystems – including the processor, storage,