Design and Performance Evaluation of a Scalable Low-Latency Three-Layer Hierarchical Data Aggregation Framework for IoT Networks
Keywords:
Data aggregation, Edge computing, Hierarchical architecture, IoT, Low latency, Scalability, Wireless sensor networksAbstract
This work investigates the design and performance evaluation of a scalable low-latency three-layer hierarchical data aggregation framework for Internet of Things (IoT) networks. The rapid growth of IoT devices and wireless sensor networks has resulted in massive data generation, creating major challenges related to scalability, network congestion, latency, bandwidth utilization, and energy efficiency. Conventional flat and two-layer network architectures often suffer from excessive routing overhead, redundant data transmission, packet collisions, and rapid energy depletion, which limit their effectiveness in large-scale IoT environments. To overcome these limitations, this paper proposes a scalable hierarchical framework designed to optimize data transmission, processing efficiency, and network reliability. The proposed architecture consists of three layers—a sensor layer for real-time data collection, an edge/aggregation layer for intermediate processing and filtering, and a cloud layer for large-scale storage and analytics. A hybrid data aggregation algorithm integrating temporal aggregation, spatial aggregation, and threshold-based filtering is introduced to reduce redundant transmissions while preserving data integrity and communication reliability. By distributing processing and routing operations across multiple layers, the framework significantly reduces communication overhead and improves scalability in dense wireless sensor network environments. Performance evaluation is conducted using MATLAB-based simulation under IEEE 802.15.4 communication standards with both periodic and event-driven traffic models. Several key performance metrics, including latency, energy consumption, throughput, packet delivery ratio (PDR), network lifetime, and control overhead, are analyzed and compared with conventional flat and two-layer architectures. Simulation results demonstrate that the proposed three-layer model reduces latency by up to 35% and energy consumption by approximately 28% while achieving higher throughput and improved packet delivery performance. The framework also maintains stable communication and efficient operation in networks containing up to 1000 sensor nodes. Overall, the proposed hierarchical framework provides an efficient, scalable, and energy-aware solution for next-generation IoT applications, including smart cities, industrial automation, environmental monitoring, and healthcare systems requiring reliable low-latency communication.
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