By Topic

Optimization of Global Data Center Thermal Management Workload for Minimal Environmental and Economic Burden

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Shah, A.J. ; Hewlett Packard Lab., Palo Alto ; Krishnan, N.

The rapid deployment of information and communications technology (ICT) across the globe has led to a network of high-density computer data centers to store, process and transmit information. These large-scale technology warehouses consume vast amounts of energy for running the compute infrastructure and auxiliary cooling resources. Recent literature has suggested the possibility of globally staggering compute workloads to take advantage of local climatic conditions as a means to reducing cooling energy costs. This paper further explores this premise by performing an in-depth analysis of the environmental and economic burden of managing the thermal infrastructure of a globally connected data center network. The paper examines a case study where the potential energy savings achievable by staggering workloads across arbitrarily chosen data centers in the U.S., India, and Russia are examined. The results show that the environmental benefit of such off-shoring is mostly dependent on the fuel mix of the grid to which the workload is transferred and the energy consumption in each location. Further, we show that dynamic optimization of the thermal workloads based on local weather patterns can reduce the environmental burden by up to 30%. The paper concludes with a detailed economic assessment. For the case study in this paper, we find that such global workload staggering can potentially reduce operational costs by nearly 35%.

Published in:

Components and Packaging Technologies, IEEE Transactions on  (Volume:31 ,  Issue: 1 )