The rapid growth of Internet of Things (IoT) devices, together with the increasing demand for real-time data processing, has exposed the limitations of traditional centralized cloud computing architectures. Edge computing has emerged as a transformative paradigm that brings computation, storage, and networking closer to the data source, thereby reducing latency, conserving bandwidth, and enhancing privacy. This paper presents a comprehensive review of edge computing as a modern trend in information technology. We systematically examine the architectural foundations, enabling technologies, and deployment models that underpin edge computing ecosystems. Furthermore, we analyze prominent application domains including autonomous vehicles, smart cities, industrial IoT (IIoT), healthcare, and augmented or virtual reality where edge computing delivers measurable performance improvements. A critical assessment of open challenges such as security vulnerabilities, resource constraints, interoperability, and orchestration complexity is also provided. Finally, we outline future research directions, including the convergence of edge computing with artificial intelligence (Edge AI), 6G networks, digital twins, and serverless edge architectures. This review aims to serve as a foundational reference for researchers and practitioners seeking to understand the current state and future direction of edge computing within the broader information technology landscape.

Keywords: Edge Computing, Internet of Things, Fog Computing, Cloud-Edge Continuum, Latency Reduction, Edge AI, Distributed Systems, Real-Time Processing.