Thermal feature extraction of servers in a datacenter using thermal image registration |
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| Affiliation: | 1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023, China;2. Network and Information Center, Dalian University of Technology, Dalian 116023, China;1. Research Institute of Electrical Communication, Tohoku University, Sendai 980-8577, Japan;2. Institute of Ultra High Frequency Semiconductor Electronics of RAS, Moscow 117105, Russia;3. Center for Photonics and Infrared Engineering, Bauman Moscow State Technical University, Moscow 111005, Russia;4. Department of Computer Science and Engineering, University of Aizu, Aizu-Wakamatsu 965-8580, Japan;5. Department of Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180, USA;1. CICAEET, School of Electronic & Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China;2. Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China;1. P.N. Lebedev Physical Institute of the Russian Academy of Sciences, Moscow 119991, Russia;2. Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141701, Russia;1. State Key Laboratories of Transducer Technology, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, PR China;2. Key Laboratory of Infrared Imaging Materials and Detectors, Shanghai Institute of Technical Physics, Chinese Academy of Sciences, PR China;3. University of Chinese Academy of Sciences, Beijing 100049, PR China;4. State Key Laboratory of Functional Materials for Informatics, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, 865 Chang Ning Rd., Shanghai 200050, PR China |
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| Abstract: | Thermal cameras provide fine-grained thermal information that enhances monitoring and enables automatic thermal management in large datacenters. Recent approaches employing mobile robots or thermal camera networks can already identify the physical locations of hot spots. Other distribution information used to optimize datacenter management can also be obtained automatically using pattern recognition technology. However, most of the features extracted from thermal images, such as shape and gradient, may be affected by changes in the position and direction of the thermal camera. This paper presents a method for extracting the thermal features of a hot spot or a server in a container datacenter. First, thermal and visual images are registered based on textural characteristics extracted from images acquired in datacenters. Then, the thermal distribution of each server is standardized. The features of a hot spot or server extracted from the standard distribution can reduce the impact of camera position and direction. The results of experiments show that image registration is efficient for aligning the corresponding visual and thermal images in the datacenter, and the standardization procedure reduces the impacts of camera position and direction on hot spot or server features. |
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| Keywords: | Datacenter Thermal image Image registration Thermal feature |
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