1,348 research outputs found
Enhancing the environmental sustainability of IT
Emerging technologies for learning report - Article exploring green I
Evolutionary Neural Network Based Energy Consumption Forecast for Cloud Computing
The success of Hadoop, an open-source
framework for massively parallel and distributed computing, is
expected to drive energy consumption of cloud data centers to
new highs as service providers continue to add new
infrastructure, services and capabilities to meet the market
demands. While current research on data center airflow
management, HVAC (Heating, Ventilation and Air
Conditioning) system design, workload distribution and
optimization, and energy efficient computing hardware and
software are all contributing to improved energy efficiency,
energy forecast in cloud computing remains a challenge. This
paper reports an evolutionary computation based modeling
and forecasting approach to this problem. In particular, an
evolutionary neural network is developed and structurally
optimized to forecast the energy load of a cloud data center.
The results, both in terms of forecasting speed and accuracy,
suggest that the evolutionary neural network approach to
energy consumption forecasting for cloud computing is highly
promising
Improving Energy Effeciency and Reliability of Disk Storage Systems
Numerous energy saving techniques have been developed to aggressively reduce energy dissipation in parallel disks. However, many existing energy conservation schemes have substantial adverse impacts on disk reliability. To remedy this deficiency, in this paper we address the problem of making tradeoffs between energy efficiency and reliability in parallel disk systems. Among several factors affecting disk reliability, the two most important factors - disk utilization and ages - are the focus of this study. We built a mathematical reliability model to quantify the impacts of disk age and utilization on failure probabilities of mirrored disk systems. In light of the reliability model, we proposed a novel concept of safe utilization zone, within which energy dissipation in disks can be reduced without degrading reliability. We developed two approaches to improving both reliability and energy efficiency of disk systems through disk mirroring and utilization control, enforcing disk drives to be operated in safe utilization zones. Our utilization-based control schemes seamlessly integrate reliability with energy saving techniques in the context of fault-tolerant systems. Experimental results show that our approaches can significantly improve reliable while achieving high-energy efficiency for disk systems under a wide range of workload situations
Power Management Techniques for Data Centers: A Survey
With growing use of internet and exponential growth in amount of data to be
stored and processed (known as 'big data'), the size of data centers has
greatly increased. This, however, has resulted in significant increase in the
power consumption of the data centers. For this reason, managing power
consumption of data centers has become essential. In this paper, we highlight
the need of achieving energy efficiency in data centers and survey several
recent architectural techniques designed for power management of data centers.
We also present a classification of these techniques based on their
characteristics. This paper aims to provide insights into the techniques for
improving energy efficiency of data centers and encourage the designers to
invent novel solutions for managing the large power dissipation of data
centers.Comment: Keywords: Data Centers, Power Management, Low-power Design, Energy
Efficiency, Green Computing, DVFS, Server Consolidatio
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