Year: 2026
Type: preprint
Abstract: The rapid growth of Internet of Things (IoT) devices has led to large-scale continuous data streams that require realtime processing. Traditional cloud-centric architectures fail to meet low-latency and bandwidth efficiency requirements due to network delays and high data transmission overhead. This paper proposes EdgeStream, a lightweight edge-based framework for real-time streaming analytics in IoT environments. The system integrates edge nodes for local processing with a cloud backend for coordination and storage, using MQTT-based communication and distributed processing with anomaly detection. Analytical models for latency, throughput, and bandwidth are developed to evaluate performance. Experimental results, compared to cloudbased systems, show up to 92.8
Source: arXiv (Cornell University)
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7164907024