Masannagudam, Praveen Reddy (2024) Enhancing Performance and Security in Mobile Cloud Computing Through Machine Learning-Based Edge Computing Integration. Masters thesis, Dublin, National College of Ireland.
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Abstract
The popularity of Mobile Cloud Computing (MCC) is facilitated by innovative implementation, and yet it suffers from persistent challenges in performance optimization as well as security. For these critical challenges in MCC environments, this research investigates how machine learning can be integrated with edge computing. We propose new approaches for resource allocation with deep reinforcement learning and advanced neural networks for security threat detection at the edge layer. This research shows through comprehensive experimentation and analysis that machine learning models can tremendously help reduce latency, improve resource utilization and detect MSS threats in MCC environments. The results provide important steps towards designing intelligent edge computing solutions alongside a framework for future mobile cloud computing optimization.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Samarawickrama, Yasantha UNSPECIFIED |
Uncontrolled Keywords: | Edge computing; Mobile cloud computing; Optimization |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning |
Divisions: | School of Computing > Master of Science in Cloud Computing |
Depositing User: | Ciara O'Brien |
Date Deposited: | 15 Jul 2025 14:25 |
Last Modified: | 15 Jul 2025 14:25 |
URI: | https://norma.ncirl.ie/id/eprint/8121 |
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