Wireless Sensor Networks for Data Centers

Non-IT loads typically account for nearly 50% of data center energy consumption. Using real-time information generated by a wireless sensor network, managers at a USDA data center in St. Louis, Missouri, were able to identify and implement changes in data center operations that reduced cooling load by 48% and overall power usage by 17%. Simple payback for the wireless sensor network was 3.4 years. View full-size infographic. [PDF - 227 KB]

GPG Findings 001, March 2012, Wireless Sensor Networks for Data Centers. Opportunity: How much energy is used by data centers in the U.S.? 2% of all U.S. Energy is consumed by data centers. Approximately 50% goes to non-it loads. Technology: How do Wireless Sensor Networks save energy? Capture and display critical information in real-time. Operators identify ways to increase energy-efficiency. Measurement and Verification. Where did measurement and verification occur? Lawrence Berkeley National Laboratory assessed the effectiveness of collecting real-time information to optimize data-center energy efficiency at the USDA National Information Technology Center in St. Louis, Missouri. Results: How did Wireless Sensor Networks perform in M and V? 17% energy savings, 48% reduction in cooling load. Effective tool for on-going optimization of data centers. 3.4 years payback at $0.045 kWh which is less than 50% of national average $0.11 kWh. Deployment: Where does M and V recommend deploying Wireless Sensor Networks? All data centers. Estimated $61 million in annual savings and annual decrease of 532,000 metric tons of Carbon Dioxide, if implemented by tenant agencies throughout the GSA portfolio. Data center assessment kit developed during study reduces deployment time and power interruptions during installation. [PDF - 227 KB]

Reference above to any specific commercial product, process or service does not constitute or imply its endorsement, recommendation or favoring by the United States Government or any agency thereof.

print Share Icon Last Reviewed 2018-08-15