Integrating Edge Computing with Cloud Networking: Architectural Models, Use Cases, and Performance Metrics

Abstract

Integrating edge computing with cloud networking represents a transformative approach to enhancing the performance, scalability, and responsiveness of distributed computing environments. This study explores various architectural models that facilitate the seamless integration of edge and cloud infrastructures, including hybrid edge-cloud architectures and edge-native frameworks. Key use cases are examined to demonstrate the practical applications and benefits of this integration, such as real-time analytics, IoT deployments, and latency-sensitive applications like autonomous vehicles and augmented reality. Additionally, performance metrics are analyzed to evaluate the effectiveness of integrated edge-cloud solutions, focusing on latency reduction, bandwidth efficiency, and computational load distribution. By combining edge computing's proximity advantages with cloud networking's robust processing capabilities, organizations can achieve optimized data processing, improved user experiences, and enhanced operational efficiency. This comprehensive analysis provides valuable insights into the potential of edge-cloud integration to address the evolving demands of modern digital ecosystems.