Green Data Centers in Computing Energy Efficiency: A Bibliometric Analysis
DOI:
https://doi.org/10.58812/wsshs.v4i08.3099Keywords:
Bibliometric Analysis, Cloud Computing, Energy Efficiency, Green Computing, Green Data CentersAbstract
Green data centers have become a central concern in computing infrastructure management as organizations pursue energy efficiency alongside environmental sustainability. In this study, an attempt is made to conduct a bibliometric analysis to investigate the intellectual structure, research trends, key contributors, and emerging themes in green data center and computing energy efficiency scholarship. The data were collected from the Scopus database using keywords “green data center”, “green computing”, and “energy efficiency” and analyzed using VOSviewer to conduct co-occurrence analysis, citation analysis, co-authorship analysis, institutional collaboration analysis, and country collaboration mapping. The results show that green computing, energy efficiency, and data centers form the core themes linked with cloud computing, virtual machine consolidation, cooling systems, and renewable energy integration. Based on citation analysis, key contributions such as energy-aware resource allocation heuristics, dynamic virtual machine consolidation algorithms, and thermal-aware cooling strategies significantly influence the field. The collaboration analysis demonstrates that the United States, China, India, and the United Kingdom serve as major contributors to the global research network, supported by a small group of highly prolific scholars, while institutional affiliation reporting across the field remains fragmented and generically labeled. Furthermore, thematic evolution indicates a transition from infrastructure-level cooling and consolidation concerns toward machine-learning-driven scheduling and carbon-aware resource management. This study contributes by providing comprehensive mapping of green data center research development and identifying critical research gaps for future scholarship, particularly in integrating renewable energy with intelligent workload orchestration.
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