Novel methodologies for mobile application performance monitoring in banking services
Posted: Mar 08, 2022
Abstract
This research introduces a groundbreaking framework for mobile application performance monitoring specifically tailored to the unique demands of banking services. Traditional monitoring approaches have proven inadequate for the complex, security-sensitive, and real-time nature of financial mobile applications, which must balance performance optimization with stringent regulatory compliance and data protection requirements. Our novel methodology integrates quantum-inspired anomaly detection algorithms with federated learning techniques to enable comprehensive performance assessment without compromising sensitive financial data. The approach leverages bio-inspired optimization principles drawn from swarm intelligence to dynamically adapt monitoring parameters based on application usage patterns and transaction volumes. We developed a cross-platform monitoring architecture that operates across iOS and Android ecosystems while maintaining consistent performance metrics. The system employs unconventional temporal analysis that considers both microsecond-level transaction processing and longitudinal performance trends over extended periods. Our results demonstrate a 47
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