Edge Computing for Intelligent IoT Systems: Architecture, Security, and Performance Optimization

Abstract

The rapid expansion of Internet of Things (IoT) devices has generated enormous volumes of data that must be processed efficiently to support real-time applications. Traditional cloud computing architectures often require data to be transmitted to centralized servers, which can introduce latency, network congestion, bandwidth limitations, and dependency on remote infrastructure. Edge computing provides an alternative architecture by moving computational resources closer to data-generating devices. This article examines the role of edge computing in intelligent IoT environments and analyzes its architectural characteristics, performance benefits, security requirements, and deployment challenges. The study discusses the interaction between IoT devices, edge nodes, gateways, and cloud platforms and examines how distributed processing can improve response time and reduce communication overhead. Particular attention is given to resource management, data processing, scalability, fault tolerance, and secure communication. The article proposes a conceptual edge-IoT architecture in which time-sensitive processing is performed locally while computationally intensive or long-term analytical tasks are transferred to cloud infrastructure.