Optimizing Data Processing Through Edge-Cloud Integration: A Comprehensive Framework

Abstract

This article presents a comprehensive analysis of hybrid edge-cloud architectures in modern distributed computing systems, focusing on the synergistic integration of edge and cloud computing paradigms. The study examines the fundamental principles, implementation strategies, and challenges in creating efficient hybrid processing environments. Through detailed analysis of real-world case studies across autonomous vehicles, maritime operations, and healthcare sectors, we demonstrate the practical applications and benefits of hybrid processing approaches. The research encompasses technical specifications of algorithms, protocols, and frameworks essential for implementing robust hybrid systems. The investigation reveals both the current limitations of hybrid architectures and potential solutions through emerging technologies. The article proposes strategies for addressing these challenges through advanced connectivity solutions, AI-driven optimization, enhanced security frameworks, and architectural innovations. This article contributes to the growing body of knowledge in distributed computing by offering a structured approach to implementing and optimizing hybrid edge-cloud processing solutions while considering future technological advancements.