Development of A Control Delay Layer for Data Transmission Stability in Remote Patient Monitoring System

Ahmad Sidik  Rofiudin; Tien Fabrianti  Kusumasari; Sinung  Suakanto

doi:10.59395/ijadis.v7i1.1509

Authors

Ahmad Sidik Rofiudin Information System, Telkom University, Indonesia
Tien Fabrianti Kusumasari Information System, Telkom University, Indonesia
Sinung Suakanto Information System, Telkom University, Indonesia

DOI:

https://doi.org/10.59395/ijadis.v7i1.1509

Keywords:

Backend System, Data Transmission Stability, Digital Health System, Load Testing, Remote Patient Monitoring

Abstract

Remote Patient Monitoring (RPM) systems generate continuous health data that must be reliably processed at the backend to support timely clinical decision-making. Many real-world RPM deployments rely on synchronous request handling, which can lead to service degradation and request failures under high concurrency. This study designed and evaluated a Control Delay Layer (CDL) as an application-layer mechanism to improve backend request-handling stability in a web-based RPM system. The proposed mechanism decouples data reception from permanent storage through temporary buffering and deferred batch processing while regulating data submission behavior at the service level. System behavior before and after CDL implementation was examined using controlled load testing under identical scenarios. The evaluation employed service-level performance metrics, including request failure rate, response time distribution, and computational resource utilization. Experimental results show that the baseline monolithic system experienced an average request failure rate of approximately 14% under peak load, whereas no request failures were observed after CDL implementation. The CDL enabled system maintained consistent response-time behavior and stable resource utilization at higher concurrency levels. These findings demonstrate that backend-level request-handling control can effectively enhance system stability under high load conditions without requiring device-level modifications, providing a complementary approach for scalable and resilient digital health systems.

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