A Performance-Optimized Client-Server Synchronization Framework for Real-Time Consumer Mobile Applications

Authors

  • Vihit shah Staff Engineer, CVS Health, NY, USA Author

DOI:

https://doi.org/10.15662/IJARCST.2021.0406015

Keywords:

Client-Server Synchronization, Differential Updates, Optimistic UI, Conflict Resolution Engine, Version Vectors, Real-Time Mobile Applications, Eventual Consistency

Abstract

Real-time consumer mobile applications, such as collaborative productivity tools, social media feeds, and mobile gaming, heavily rely on seamless and low-latency client-server data synchronization to maintain data consistency and provide an optimal user experience. Traditional synchronization approaches, often polling-based or relying on naive full-state updates, are inefficient, consume excessive network bandwidth and device battery, and introduce perceptible lag, especially under intermittent network conditions common to mobile users. This paper proposes a Performance-Optimized Client-Server Synchronization Framework (POCSF) that employs a hybrid strategy combining differential synchronization, optimistic UI updates, and predictive data pre-synchronization. The framework leverages a server-side Conflict Resolution Engine (CRE) with a version-vector-based approach to ensure eventual consistency without blocking the client. An empirical evaluation, conducted on a simulated real-time chat application, demonstrates that POCSF achieves a $75\%$ reduction in network data transfer and a $58\%$ improvement in perceived UI responsiveness (measured by Time-to-Interaction after local change) compared to a traditional polling-based synchronization model. Furthermore, the framework maintains strong eventual consistency with an average conflict resolution time of less than $50 \text{ms}$, establishing a robust blueprint for developing highly responsive and efficient mobile applications.

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Published

2021-12-15

How to Cite

A Performance-Optimized Client-Server Synchronization Framework for Real-Time Consumer Mobile Applications. (2021). International Journal of Advanced Research in Computer Science & Technology(IJARCST), 4(6), 5882-5886. https://doi.org/10.15662/IJARCST.2021.0406015