Minimal Green Energy Consumption and Workload Management for Data Centers on Smart City Platforms

Pei Pei, Zongjie Huo, Oscar Sanjuán Martínez and Rubén González Crespo
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Pei Pei: School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China
Zongjie Huo: School of Economics and Management, Lanzhou University of Technology, Lanzhou 730050, China
Oscar Sanjuán Martínez: Computer Science Department, School of Engineering and Technology, Universidad Internacional de La Rioja, 26006 Logroño, La Rioja, Spain
Rubén González Crespo: Computer Science Department, School of Engineering and Technology, Universidad Internacional de La Rioja, 26006 Logroño, La Rioja, Spain

Sustainability, 2020, vol. 12, issue 8, 1-14

Abstract: Presently, energy is considered a significant resource that grows scarce with high demand and population in the global market. Therefore, a survey suggested that renewable energy sources are required to avoid scarcity. Hence, in this paper, a smart, sustainable probability distribution hybridized genetic approach (SSPD-HG) has been proposed to decrease energy consumption and minimize the total completion time for a single machine in smart city machine interface platforms. Further, the estimated set of non-dominated alternative using a multi-objective genetic algorithm has been hybridized to address the problem, which is mathematically computed in this research. This paper discusses the need to promote the integration of green energy to reduce energy use costs by balancing regional loads. Further, the timely production of delay-tolerant working loads and the management of thermal storage at data centers has been analyzed in this research. In addition, differences in bandwidth rates between users and data centers are taken into account and analyzed at a lab scale using SSPD-HG for energy-saving costs and managing a balanced workload.

Keywords: load balancing; green energy; genetic algorithm; renewable energy (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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