Energy-efficient Computing for Big Data

Overview

Energy-efficient computing for big data is a technology that allows for the efficient use of computing power when dealing with large amounts of data. It combines software and hardware techniques to minimize energy consumed during data processing, allowing for the storage and processing of the immense amounts of data that are generated by the internet of things (IoT), artificial intelligence (AI) and machine learning (ML) applications. Energy-efficient computing for big data is becoming increasingly important as data processing needs grow and is essential for the continued growth of IoT, AI and ML technology. This technology uses hardware and software techniques to reduce energy consumption during data processing, resulting in the ability to store and process large amounts of data more quickly and efficiently. This ultimately leads to cost savings for businesses and consumers.

Research published in this journal

2 peer-reviewed articles, ranked by relevance. Each links to its DOI.

How this research is being cited

The 2 articles above have been cited 8 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.

• An Architectural Optimization Framework for Scalable Spatial Clustering in High-Redundancy Environments
  2026 · Technologies
• Clustering of the Air Pollution Standard Index (ISPU) in the Province of DKI Jakarta Using the CLARANS Algorithm
  A. Azzahra et al. · 2025 · JOURNAL OF APPLIED INFORMATICS AND COMPUTING
• Analysis of Data Mining Techniques and Algorithms on Diabetes Dataset
  2025 · EAI Endorsed Transactions on Pervasive Health and Technology
• Extraction of association rules in a diabetic dataset using parallel FP-growth algorithm under apache spark
  Y. Fakir et al. · 2024 · International Journal of Informatics and Communication Technology (IJ-ICT)
• A Comparative Study of Clustering Approaches on Segmentation for Construction Remodeling
  2023 ·
• A Comparative Study of Clustering Approaches on Segmentation for Construction Remodeling
  D. Neguja et al. · 2023 · International Conference on Innovative Mechanisms for Industry Applications
• Role and Challenges of Unstructured Big Data in Healthcare
  2019 · Advances in intelligent systems and computing

A sample of recent works citing this journal's research on Energy-efficient Computing for Big Data, linking to each citing work.

This page summarises published research for orientation; it is not medical or professional advice.

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