Edge Computing Architectures for Real-Time IoT Applications

Abstract

Edge computing has emerged as a transformative architecture for real-time Internet of Things (IoT) applications by bringing computational and storage resources closer to the data source. This paradigm reduces latency, bandwidth usage, and energy consumption while improving data privacy and reliability. Traditional cloud-based systems are increasingly challenged by the vast scale of IoT data, making edge computing a vital solution for time-sensitive applications such as autonomous vehicles, healthcare monitoring, and industrial automation. This paper presents a comprehensive analysis of edge computing architectures, highlighting their core components, design considerations, benefits, and challenges. The discussion also explores the integration of edge and cloud computing for achieving scalable and low-latency IoT solutions.