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The Future of Hybrid Cloud Infrastructures in Data Engineering for Scalable Recommender Systems

by Deexith Reddy, Rohan Singh Rajput
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 31
Year of Publication: 2023
Authors: Deexith Reddy, Rohan Singh Rajput
10.5120/ijca2023923067

Deexith Reddy, Rohan Singh Rajput . The Future of Hybrid Cloud Infrastructures in Data Engineering for Scalable Recommender Systems. International Journal of Computer Applications. 185, 31 ( Aug 2023), 1-4. DOI=10.5120/ijca2023923067

@article{ 10.5120/ijca2023923067,
author = { Deexith Reddy, Rohan Singh Rajput },
title = { The Future of Hybrid Cloud Infrastructures in Data Engineering for Scalable Recommender Systems },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2023 },
volume = { 185 },
number = { 31 },
month = { Aug },
year = { 2023 },
issn = { 0975-8887 },
pages = { 1-4 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number31/32889-2023923067/ },
doi = { 10.5120/ijca2023923067 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:29:00.213806+05:30
%A Deexith Reddy
%A Rohan Singh Rajput
%T The Future of Hybrid Cloud Infrastructures in Data Engineering for Scalable Recommender Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 31
%P 1-4
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper explores the future of hybrid cloud infrastructures in data engineering for scalable recommender systems. It delves into the opportunities and challenges presented by hybrid clouds, focusing on their role in managing large volumes of data and complex computational tasks. The paper discusses the advantages of hybrid clouds, such as scalability, flexibility, and costeffectiveness, and their potential to enhance the efficiency and accuracy of recommender systems. It also addresses the challenges associated with implementing hybrid clouds, including data privacy, resource management, and compatibility issues. The paper concludes by highlighting the promising future of hybrid cloud infrastructures in driving significant advancements in data engineering and their potential impact on various sectors.

References
  1. A. Z. A. Bakar and A. A. Manaf. Hybrid cloud challenges and solutions in recommender systems. arXiv preprint arXiv:2208.12759, 2023.
  2. Utkarsh Gupta, Steven Hsia, Vineet Saraph, Xiang Wang, Brendan Reagen, Gang Wei, Han Lee, David Brooks, and Chun Wu. Deeprecsys: A system for optimizing end-to-end at-scale neural recommendation inference. arXiv preprint arXiv:2001.02772, 2020.
  3. Mohammad Khalaj and Chawki Dadkhah. FNHSM HRS: Hybrid recommender system using fuzzy clustering and heuristic similarity measure. arXiv preprint arXiv:1909.13765, 2019.
  4. Mohammad Khalaj and Nima Mohammadnejad. FCNHSMRA HRS: Improve the performance of the movie hybrid recommender system using resource allocation approach. arXiv preprint arXiv:1908.05608, 2019.
  5. Chawki Labba and Nour-Eddine Ben Saoud. Cost-based assessment of partitioning algorithms of agent-based systems on hybrid cloud environments. arXiv preprint arXiv:1709.05708, 2017.
  6. Aimin Li, Xu Yang, Hui Wang, Yu Zhang, Wei Zhang, Xudong Chen, and Haitao Zhang. The fundamentals of hybrid cloud. Nature Electronics, 3(8):417–422, 2020.
  7. Yaser Mansouri, Vladyslav Prokhorenko, and Muhammad A Babar. An automated implementation of hybrid cloud for performance evaluation of distributed databases. arXiv preprint arXiv:2006.02833, 2020.
  8. Peter Mell and Tim Grance. The nist definition of cloud computing. Special Publication 800-145, 2011.
  9. Zia Rahman, Anjali I Swapna, Hasan R Habib, and Ahmed Shaoun. Performance evaluation of fuzzy integrated firewall model for hybrid cloud based on packet utilization. arXiv preprint arXiv:2006.12736, 2020.
  10. Fahad Ullah, Sandeep Dhingra, Xiao Xia, and Muhammad A Babar. Evaluation of distributed data processing frameworks in hybrid clouds. arXiv preprint arXiv:2201.01948, 2022.
  11. Ankit Verma, Ludmila Cherkasova, and Robert H Campbell. Aria: Automatic resource inference and allocation for mapreduce environments. pages 235–244, 2011.
  12. Ming Zhang, Rajiv Ranjan, Suresh Nepal, Markus Menzel, and Andreas Haller. A declarative recommender system for cloud infrastructure services selection. arXiv preprint arXiv:1210.2047, 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Cloud Computing Data Engineering Information Retrieval Scalability