An Integrative Approach to Implementing Green Cloud Computing, Artificial Intelligence, and Big Data Management in Modern Library Systems
Keywords:
Digital Libraries, Green Cloud Computing, Artificial Intelligence (AI), Big Data Management, Data Storage and ManagementAbstract
The expansion of digital resources and the integration of emerging technologies have significantly transformed modern library systems. With the rise in digital collections, libraries are now dealing with a vast amount of data that needs efficient management and storage. This research will explore the role and benefits of leveraging green cloud computing, artificial intelligence, and big data management to improve efficiency and sustainability in library science. This research explores the integrative implementation of green cloud computing, artificial intelligence, and big data management to enhance the efficiency, user engagement, and environmental sustainability of modern libraries. These libraries house a broad range of resources, including music files, research content, reading articles, and other entertainment material.
References
Anderson T, editor. The Theory and Practice of Online Learning. Athabasca, Alberta, Canada: Athabasca University Press; 2008.
Bawden D, Robinson L. Introduction to Information Science. London, UK: Facet Publishing; 2015.
Buyya R, Yeo CS, Venugopal S. Market-oriented cloud computing: vision, hype, and reality for delivering it services as computing utilities. In: 2008 10th IEEE international conference on high performance computing and communications, Dalian, China, September 25–27, 2008. pp. 5–13.
Li F, Zhang J. Case study: a metadata scheme for multi-type manuscripts for the TD Lee Archives Online. Library Hi Tech. 2014; 32 (2): 219–228.
Beloglazov A, Buyya R. Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers. Concurr Comput Pract Experience. 2012; 24 (13): 1397–1420.
Tedd LA. E-books in academic libraries: an international overview. New Rev Acad Librarianship. 2005; 11 (1): 57–79.
Grispos G, Storer T, Glisson WB. Calm before the storm: the challenges of cloud computing in digital forensics. Int J Digital Crime Forens. 2012; 4 (2): 28–48.
Zhang Y. Searching for specific health‐related information in Medline Plus: behavioral patterns and user experience. J Assoc Inform Sci Technol. 2014; 65 (1): 53–68.
Kroski E. The Makerspace Librarian's Sourcebook. Chicago, IL, USA: ALA American Library Association; 2017.
He D, Kumar N, Wang H, Wang L, Choo KK, Vinel A. A provably-secure cross-domain handshake scheme with symptoms-matching for mobile healthcare social network. IEEE Trans Dependable Secure Comput. 2016; 15 (4): 633–645.
Goodfellow I, Bengio Y, Courville A. Deep Learning. Cambridge, MA, USA: MIT Press; 2016.
Halevi G, Moed HFDr. The evolution of big data as a research and scientific topic: overview of the literature. Res Trends. 2012; 1 (30): Article 2.
Kitchin R. Big data, new epistemologies and paradigm shifts. Big Data Soc. 2014; 1 (1): 2053951714528481.
Liao SH, Chu PH, Hsiao PY. Data mining techniques and applications–a decade review from 2000 to 2011. Expert Syst Appl. 2012; 39 (12): 11303–11311.
Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A. Cloud computing—the business perspective. Decis Support Syst. 2011; 51 (1): 176–189.
Mell P, Grance T. The NIST Definition of Cloud Computing. Special Publication 800-145. Gaithersburg, MD, USA: National Institute of Science and Technology; 2011.
