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Indexed by:期刊论文

Date of Publication:2013-05-01

Journal:JOURNAL OF SUPERCOMPUTING

Included Journals:SCIE、EI、Scopus

Volume:64

Issue:2

Page Number:383-408

ISSN No.:0920-8542

Key Words:Data center; Thermal management; Thermal camera networks; Energy consumption; Fine-grained data collection

Abstract:Thermal cameras provide fine-grained thermal information that enables monitoring and autonomic thermal management in large datacenters. The real-time thermal monitor network employing thermal cameras is proposed to cooperatively localize hotspots and extract their characteristics (i.e., temperature, size, and shape). These characteristics are adopted to classify the causes of hotspots and make energy-efficient thermal management decisions such as job migration. Specifically, a sculpturing algorithm for extracting and reconstructing shape characteristics of hotspots is proposed to minimize the network overhead. Experimental results show the validity of all the algorithms proposed in this paper.