Adaptive Resource Management Strategies for High-Traffic Android Applications
Varun Reddy Guda · Journal of Artificial Intelligence Machine Learning and Data Science · 2025
The exponential growth of mobile application users has created unprecedented challenges in resource management for Android applications.When applications scale from thousands to millions of concurrent users, traditional resource management approaches become inadequate, leading to performance degradation, crashes and poor user experience.This paper presents comprehensive adaptive resource management strategies specifically designed for high-traffic Android applications.Our research methodology combines theoretical analysis with empirical testing across multiple high-traffic scenarios, demonstrating measurable improvements in application stability and performance.The proposed framework introduces dynamic resource allocation mechanisms, intelligent memory management systems and predictive scaling algorithms that collectively reduce crash rates by up to 87% while maintaining optimal performance under extreme load conditions.These strategies have been validated across diverse Android device configurations and network environments, proving their effectiveness in real-world deployment scenarios.