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incentive-scheduling algorithms to Provide Green Computational Data Center

SN Computer Science 2021年第4期2卷 252页

作者： Haruna, Ahmed Abba Jung, Low Tan Arputharaj, Vijay Muhammad, L.J. College of Computer Science and Engineering University of Hafr Al Batin Al Jamiah Hafar Al Batin 39524d Saudi Arabia High Performance Computing Cloud Centre Universiti Teknologi PETRONAS Seri Iskandar Perak 32610 Malaysia Faculty of Science and Information Technology Skyline University Nigeria No. 2 Zaria Road Kano Nigeria Mathematics and Computer Science Department Federal University Kashere Gombe State Kashere Nigeria

The increased computational loads in grid servers are dissipating more heat to eventually amplifies the cooling demand in the data center (DC). This can lead to more submitted jobs missing their job completion deadlines. Unfortunately, the conventional DC job scheduling approaches do not provide compensation to the resource users on their submitted jobs that missed the deadlines. The absence of compensation may dissuade users from submitting jobs to the DCs. While the free air-cooling strategy is used elsewhere, it is not generally applicable in tropical countries such as Malaysia. A constant artificial cooling (air conditioning) is needed to sustain the DC long-hour operation. To solve this issue in the tropical region, green incentive-scheduling algorithms were devised to significantly save the cooling electricity consumption cost in DC and to be able to compensate users (as an incentive) for their submitted jobs that missed the job completion deadline(s). However, there is a need to further analyse the performance of the proposed green incentive-scheduling algorithms using a different benchmark traces file and to conduct a cost-saving comparison analysis between the green incentive-scheduling and the non-green incentive-scheduling algorithms. Therefore, this paper's authors observed and analysed the performance comparison of the proposed green incentive-based job scheduling algorithms using a benchmark traces file and conducted a cost-saving comparison analysis between the green incentive and the non-green incentive-based scheduling algorithms. Ultimately, the green incentive-scheduling algorithms are to show their impact on reducing the DC operation costs (e.g. electricity bills for cooling) and to provide fair compensation to grid users for a win–win situation. © 2021, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Data center Green computing incentive-based job scheduling algorithm Server Temperature

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