Energy-Efficient Algorithms for Sustainable Big Data Processing and Green Computing
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V4I4P101Keywords:
Energy-efficient computing, big data processing, green computing, energy-aware algorithms, sustainable data centers, task scheduling, data management, hardware optimization, renewable energy integration, carbon footprint reductionAbstract
The exponential growth of big data has led to significant energy consumption and environmental concerns. This paper explores the development and implementation of energy-efficient algorithms to promote sustainable big data processing and green computing. We discuss the challenges and opportunities in this domain, present a comprehensive review of existing energy-efficient algorithms, and propose novel approaches to further reduce energy consumption. The paper includes a detailed analysis of the energy consumption in data centers, the impact of data processing algorithms, and the role of hardware optimization. We also introduce a new algorithm, the Energy-Aware Data Processing (EADP) algorithm, and evaluate its performance through simulations and real-world case studies. Finally, we discuss future research directions and the potential for widespread adoption of energy-efficient practices in the industry
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