Leveraging machine learning for real-time optimization in large-scale information systems
*Swati G. KaleCorresponding authorswati79kale@gmail.comDepartment of Information TechnologyYeshwantrao Chavan College of EngineeringNagpur, Maharashtra, 441110, IndiaView full profile → , Smita N. Gambhiresmita.gambhire@bharatividyapeeth.eduDepartment of Computer ApplicationAbhijit Kadam Institute of Management and Social SciencesBharati Vidyapeeth (Deemed to be) UniversitySolapur, Maharashtra, 413004, IndiaView full profile → , Deepti Deshmukhdeepti.deshmukh@bharatividyapeeth.eduInstitute of Management and Entrepreneurship DevelopmentBharati Vidyapeeth (Deemed to be) UniversityPune, Maharashtra, 411038, IndiaView full profile → , Dharmesh Dhabliyadharmesh.dhabliya@viit.ac.inDepartment of Information TechnologyVishwakarma Institute of TechnologyPune, Maharashtra, 411037, IndiaView full profile → , Yeshil Bangeraybang1@unh.newhaven.eduDepartment of Data Science and EngineeringUniversity of New HavenWest Haven, 06516, United StatesView full profile → , D. J. Dahigaonkardahigaonkardj@rknec.eduDepartment of Electronics and Communication EngineeringRamdeobaba UniversityNagpur, Maharashtra, 440013, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 09 Oct 2024
- Published Online:
- 31 May 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1990
- Pages:
- 1289–1301
Abstract
Keywords
Subject Classifications
References
[1] Musunuri, A. Chhapola, and S. Jain, “Optimizing High-Speed Serial Links for Multicore Processors and Network Interfaces,” Modern Dynamics: Mathematical Progressions, vol. 1, no. 2, pp. 31–43 (2024).
[2] E. V. N. Pamadi, “Designing efficient algorithms for MapReduce: A simplified approach,” TIJER, vol. 8, no. 7, pp. 23-37 (2021).
[3] T. Axtell, “Machine learning in complex systems,” Proceedings of the SPIE 10635, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR IX, 2018.
[4] A. Tangudu, P. K. G. Pandian, and S. Jain, “Developing Scalable APIs for Data Synchronization in Salesforce Environments,” Modern Dynamics: Mathematical Progressions, vol. 1, no. 2, pp. 44–57 (2024).
[5] S. Mahimkar, P. Pandey, and O. Goel, “Utilizing Machine Learning for Predictive Modelling of TV Viewership Trends,” International Journal of Creative Research Thoughts (IJCRT), vol. 10, no. 7, pp. f407-f420 (Jul. 2022).
[6] K. Zhang, T. Qu, D. Zhou, H. Jiang, Y. Lin, P. Li, H. Guo, Y. Liu, C. Li, and G. Q. Huang, “Digital twin-based opti-state control method for a synchronized production operation system,” Robotics and Computer-Integrated Manufacturing, vol. 63, p. 101892 (2020).
[7] V. B. R. Bhimanapati, S. Jain, and A. Aggarwal, “Agile Methodologies in Mobile App Development for Real-Time Data Processing,” Modern Dynamics: Mathematical Progressions, vol. 1, no. 2, pp. 72–88 (2024).
[8] Z. Zhang, D. Zhang, and R. C. Qiu, “Deep reinforcement learning for power system applications: An overview,” CSEE Journal of Power and Energy Systems, vol. 6, no. 1, pp. 213–225 (2019).
[9] J. Zhou, J. Sun, P. Cong, Z. Liu, X. Zhou, T. Wei, and S. Hu, “Security-critical energy-aware task scheduling for heterogeneous real-time MPSoCs in IoT,” IEEE Transactions on Services Computing, vol. 13, no. 4, pp. 745–758 (2019).
[10] Y. Hua, Z. Zhao, R. Li, X. Chen, Z. Liu, and H. Zhang, “Deep learning with long short-term memory for time series prediction,” IEEE Communications Magazine, vol. 57, no. 6, pp. 114–119 (2019).
[11] J. Ibarz, J. Tan, C. Finn, M. Kalakrishnan, P. Pastor, and S. Levine, “How to train your robot with deep reinforcement learning: lessons we have learned,” The International Journal of Robotics Research, vol. 40, no. 4–5, pp. 698–721 (2021).
[12] D. Adams and T. Krulicky, “Artificial intelligence-driven big data analytics, real-time sensor networks, and product decision-making information systems in sustainable manufacturing internet of things,” Economics, Management and Financial Markets, vol. 16, no. 3, pp. 81–93 (2021).
[13] A. O. Al-Abbasi, A. Ghosh, and V. Aggarwal, “Deeppool: Distributed model-free algorithm for ridesharing using deep reinforcement learning,” IEEE Transactions on Intelligent Transportation Systems, vol. 20, no. 12, pp. 4714–4727 (2019).




