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A green energy-efficient scheduling algorithm using the DVFS technique for cloud datacenters
Affiliation:1. Guangdong Police College, Guangzhou 510440, China;2. Institute of Software Application Technology, Guangzhou & CAS, Guangzhou, 511458, China;3. School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China;4. Electric Power Research Institute of Guangdong Power Grid Co. Ltd., Guangzhou 510600, China;1. Department of Computer Science, Rutgers University, USA;2. Universitat Politecnica de Catalunya and Barcelona Supercomputing Center, Spain;1. 11529 128, Section 2, Academia Road, Nankang, Taipei, Taiwan;2. 10617 1, Section 4, Roosevelt Road, Taipei, Taiwan;3. 31040 195, Section 4, Chung Hsing Road, Chutung, Hsinchu, Taiwan;1. Department of Computing Science, Umeå University, SE-901 87 Umeå, Sweden;2. School of Computing, National University of Singapore, 13 Computing Drive, Singapore 117417, Singapore
Abstract:Information and communication technology (ICT) has a profound impact on environment because of its large amount of CO2 emissions. In the past years, the research field of “green” and low power consumption networking infrastructures is of great importance for both service/network providers and equipment manufacturers. An emerging technology called Cloud computing can increase the utilization and efficiency of hardware equipment. The job scheduler is needed by a cloud datacenter to arrange resources for executing jobs. In this paper, we propose a scheduling algorithm for the cloud datacenter with a dynamic voltage frequency scaling technique. Our scheduling algorithm can efficiently increase resource utilization; hence, it can decrease the energy consumption for executing jobs. Experimental results show that our scheme can reduce more energy consumption than other schemes do. The performance of executing jobs is not sacrificed in our scheme. We provide a green energy-efficient scheduling algorithm using the DVFS technique for Cloud computing datacenters.
Keywords:Cloud computing  Scheduling algorithm  Dynamic voltage frequency scaling  Datacenters
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