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[ASME ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems - San Francisco, California, USA (Monday 27 August 2018)] ASME 2018 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems - Improving Energy Efficiency in Data Centers by Controlling Task Distribution and Cooling
摘要： The rapid growth in cloud computing, the Internet of Things (IoT), and data processing via Machine Learning (ML), have greatly increased our need for computing resources. Given this rapid growth, it is expected that data centers will consume more and more of our global energy supply. Improving their energy efficiency is therefore crucial. One of the biggest sources of energy consumption is the energy required to cool the data centers, and ensure that the servers stay within their intended operating temperature range. Indeed, about 40% of a data center’s total power consumption is for air conditioning[1]. Here, we study how the server air inlet and outlet, as well as the CPU, temperatures depend upon server loads typical of real Internet Protocol (IP) traces. The trace data used here are from Google clusters and include the times, job and task ID, as well as the number and usage of CPU cores. The resulting IT loads are distributed using standard load-balancing methods such as Round Robin (RR) and the CPU utilization method. Experiments are conducted in the Data Center Laboratory (DCL) at the Georgia Institute of Technology to monitor the server outlet air temperature, as well as real-time CPU temperatures for servers at different heights within the rack. Server temperatures were measured by on-line temperature monitoring with Xbee, Raspberry PI, Arduino, and hot-wire anemometers. Given that the temperature response varies with server position, in part due to spatial variations in the cooling airflow over the rack inlet and the server fan speeds, a new load-balancing approach for spatially varying that accounts temperature response within a rack is tested and validated in this paper.
关键词： Wireless Sensor System,Load Balancing,Data Center
更新于2025-09-09 09:28:46
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[IEEE 2018 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - Chengdu, China (2018.5.7-2018.5.11)] 2018 International Conference on Microwave and Millimeter Wave Technology (ICMMT) - A Low Power Consumption Wireless Sensor System with Wireless Power Harvesting for Oil Pipeline Monitoring
摘要： In this paper, a low power wireless sensor system for oil pipeline monitoring based on wireless energy harvesting is discussed. The system uses vibration sensor to detect the vibration state of the oil pipeline, and transmits the information to the sink node through the low power wireless sensor node which is supplied by wireless energy harvesting and rechargeable battery. Based on the introduction of the whole system construction, this paper focuses on the design of low-power wireless sensor nodes, including wireless energy harvesting, low-power wireless node circuit and low-power transmission protocol. The test results show that low power design strategy and wireless energy harvesting as energy supplement can effectively improve the practicability of the system.
关键词： wireless energy harvesting,oil pipeline monitoring,wireless sensor system,low power
更新于2025-09-04 15:30:14