Design and Implementation of Distributed Parallel Architecture for IoT-Based Smart Home Network Traffic Optimization

Hariani Ma’tang Pakka; Andi Adillah Firstania Azis; Fadel Muhammad Husain; Irfan Pratama Putra; Tanridio Silviati Delfina Abdurrahman; Saidah Suyuti

doi:10.31963/elekterika.v22i1.5476

Authors

Hariani Ma’tang Pakka Universitas Muslim Indonesia
Andi Adillah Firstania Azis Universitas Muslim Indonesia
Fadel Muhammad Husain Universitas Muslim Indonesia
Irfan Pratama Putra Universitas Muslim Indonesia
Tanridio Silviati Delfina Abdurrahman Universitas Muslim Indonesia
Saidah Suyuti Universitas Muslim Indonesia

DOI:

https://doi.org/10.31963/elekterika.v22i1.5476

Keywords:

Internet of Things, smart home, distributed parallel architecture, traffic management, system reliability

Abstract

The increasing implementation of Internet of Things (IoT) in 5G technology and cellular communications faces significant challenges regarding data traffic load and network congestion, particularly in conventional smart home systems. This research proposes and implements a distributed parallel smart home architecture as a solution for optimizing data traffic management and enhancing system reliability. The developed architecture adopts a three-layer structure: a cloud layer as the parent node, a route layer based on ESP8266 as distributed nodes, and a leaf layer consisting of sensors and actuators. Implementation was conducted through a prototype model at the UMI Electrical Engineering Laboratory with comprehensive system performance testing. Results demonstrate a 47% reduction in traffic load compared to conventional centralized systems, achieving 99.7% reliability with a 2.3-second recovery time. The system maintains bandwidth utilization below 60% and demonstrates scaling capability up to 200% without performance degradation. Under normal conditions, the system achieves an average traffic rate of 0.93 Kbits with a 45ms response time, while in emergency mode, it handles peak traffic up to 0.94 Kbits with a 32ms response time. This research contributes significantly to developing more efficient and scalable smart home architectures while providing a framework for implementing parallel distributed systems in broader IoT applications.

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