Emergent Architectures in Edge Computing for Low-Latency Application

Abstract

Emerging as a necessary paradigm for meeting the low-latency needs of contemporary real-time applications is edge computing. By distributing computation, storage, and network resources, edge designs reduce data transfer latency and increase system responsiveness. They are indispensible in fields including smart cities, autonomous systems, and healthcare. This study explores evolving architectural paradigms in edge computing—including layered hierarchies, microservices, and serverless computing—as well as their interfaces with technologies including 5G, IoT, and artificial intelligence. Extensive studies reveal how they allow scalable, modular, resource-efficient solutions for activities sensitive to latency. Even in this regard, security, interoperability, and resource allocation demand constant innovation notwithstanding their changing power. The work also looks at innovative ideas addressing these issues and highlights possible opportunities such federated learning and quantum computing. The outcomes highlight how crucial emergent edge computing architectures are in enabling ultra-low-latency applications and redefining operational efficiencies in many industries.