Study of Green Computing

Green Computing is an evolving practice that focuses on developing and managing information processing systems to enhance energy efficiency. Although initiatives like Energy Star have existed since the early 1990s, the increasing concerns about climate change and the energy crisis have sparked a renewed focus on sustainable computing solutions. Data centers play a major role in energy consumption, requiring power not only to run systems but also to maintain effective cooling mechanisms. This paper introduces an innovative strategy to optimize energy usage in data centers. The approach dynamically consolidates services onto fewer active servers and deactivates idle servers to save energy. We present preliminary findings on a probabilistic service allocation algorithm designed to reduce the number of active servers while maintaining the quality of service outlined in service-level agreements (SLAs). Considering the anticipated growth in data centers and their energy demands, this method shows potential for significantly reducing energy consumption.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-30
DOI
https://doi.org/10.5281/zenodo.14576293
Primary Topic
Parasite Biology and Host Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Study of Green Computing

Zenodo (CERN European Organization for Nuclear Research)
Parasite Biology and Host Interactions
article

Study of Green Computing

article en

Abstract

Green Computing is an evolving practice that focuses on developing and managing information processing systems to enhance energy efficiency. Although initiatives like Energy Star have existed since the early 1990s, the increasing concerns about climate change and the energy crisis have sparked a renewed focus on sustainable computing solutions. Data centers play a major role in energy consumption, requiring power not only to run systems but also to maintain effective cooling mechanisms. This paper introduces an innovative strategy to optimize energy usage in data centers. The approach dynamically consolidates services onto fewer active servers and deactivates idle servers to save energy. We present preliminary findings on a probabilistic service allocation algorithm designed to reduce the number of active servers while maintaining the quality of service outlined in service-level agreements (SLAs). Considering the anticipated growth in data centers and their energy demands, this method shows potential for significantly reducing energy consumption.

Zenodo (CERN European Organization for Nuclear Research)
Sant Gadge Baba Amravati University (IN)
Affordable and clean energy
Openalex Percentile: Top 54%
Parasite Biology and Host Interactions
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Study of Green Computing · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS