Edge Computing Architectures for Real-Time Distributed Processing

Abstract

Edge computing has emerged as a critical paradigm in the realm of distributed computing, particularly for real-time applications that require low latency and high reliability. This paper provides a comprehensive overview of edge computing architectures designed for real-time distributed processing. We delve into the fundamental concepts, key challenges, and state-ofthe-art solutions in the field. The paper also explores various edge computing models, including fog computing, hierarchical edge computing, and hybrid cloud-edge architectures. We present a detailed analysis of the algorithms and techniques used for task offloading, resource allocation, and data management in edge computing environments. Additionally, we discuss the performance metrics and evaluation methodologies for assessing the effectiveness of these architectures. Finally, we highlight future research directions and potential applications of edge computing in various domains such as IoT, autonomous vehicles, and smart cities