Novel Thermal-Aware Green Scheduling in Grid Environment

Abstract

The rising energy consumption of large-scale distributed computing systems raises operational expenses and has a negative impact on the environment (e.g. carbon dioxide emissions). The most expensive operating cost aspect in data centers is the electricity consumption for cooling purposes (DC). Inefficient cooling causes excessive temperatures, which leads to hardware breakdown. To solve this issue, novel thermal-aware green scheduling algorithms were developed to dramatically reduce cooling energy consumption costs while avoiding high thermal stress conditions such as big hotspots and thermal violations while preserving typical competitive performance. As a result of this research, the novel thermal-aware green scheduling algorithms can save cooling electricity usage during job execution when compared to nongreen scheduling methods. Thus, the green scheduling algorithms clearly outperform nongreen scheduling algorithms in terms of cooling power usage effectiveness.

Received: 20 July 2022 | Revised: 26 September 2022 | Accepted: 2 November 2022

Conflicts of Interest

Lawan Jibril Muhammad is an editorial board member for Artificial Intelligence and Applications, and was not involved in the editorial review or the decision to publish this article. The authors declare that they have no conflicts of interest to this work.