Abstract

Nevertheless, mobile devices harness resource poverty, which includes limited processing power, limited battery life, and limited memory storage, and this is still a considerable drawback to the provision of intensive applications, including 3D simulations and data analytics in real-time. The paper will suggest a strong three-tier hybrid architecture providing integration of mobile computing and cloud services to provide seamless delivery of education. The architecture consisted of a User Interface Tier of lightweight front-end interactions, a Middleware Tier of a Task Orchestrator and a Threshold-Based Elastic Scaling (TBES) algorithm, and a Data Tier of hybrid NoSQL storage for real-time synchronization. Created a mathematical model of energy-aware offloading to estimate the optimal point of offloading, depending on network latency and the CPU intensity locally. Simulation outcomes show that there are great performance increases in comparison with the traditional local-execution models. The TBES algorithm was able to keep the system response time at 185 ms, which is much lower than the 200 ms Rmax that is required, and even at the maximum verified load of 500 users. Furthermore, computation offloading extended mobile battery longevity by 73.3%, reducing power consumption from a 450-mW baseline to 120 mW. Bandwidth efficiency was also optimized through a differential synchronization protocol, which achieved an 88.5% reduction in data overhead. Correlation analysis using Kaggle education datasets further suggests that these technical enhancements contributed to a 22% increase in course completion rates and a 92% improvement in student engagement. These results confirm that the suggested architecture can efficiently isolate the quality of education on the one hand and the limitations of local hardware on the other, providing a solution that can be scaled to comprehensive, global e-learning.