International Journal of Science, Engineering and TechnologyAuthors: Aravind Krishnan
Abstract: Hybrid edge-cloud computing is an emerging architectural paradigm that integrates the computational power of cloud data centers with the proximity and responsiveness of edge devices. This approach addresses growing demands for real-time application performance, especially in domains such as IoT, autonomous systems, smart cities, and augmented reality. By distributing data processing between centralized cloud servers and localized edge nodes, hybrid systems can minimize latency, reduce bandwidth consumption, and improve scalability and fault tolerance. This article provides a comprehensive examination of the impact of hybrid edge-cloud computing on real-time application performance. Fundamental concepts of edge, cloud, and hybrid architectures are explored, highlighting the synergy between these paradigms in handling dynamic workloads efficiently. Key benefits such as latency reduction, bandwidth optimization, and enhanced reliability are analyzed with attention to practical real-time use cases. Challenges in orchestration, resource allocation, and security within hybrid environments are discussed, alongside technical strategies that optimize performance, including load balancing, caching, and adaptive data routing. Furthermore, the article assesses state-of-the-art frameworks and emerging trends that facilitate seamless integration of edge and cloud resources. Finally, we evaluate performance metrics and methodologies used to measure real-time responsiveness, offering insights for researchers and practitioners aiming to harness hybrid architectures for demanding, time-sensitive applications. The fusion of edge and cloud computing signifies a paradigm shift in distributed computing that promises to redefine how latency-critical applications operate in the connected world. This article serves as an essential resource capturing the multidimensional impact of hybrid edge-cloud computing on real-time application performance.
DOI: http://doi.org/10.5281/zenodo.17709228
