Hybrid Cloud Edge Computing – An Analysis of Automation and Scalability as Features that Enhance the Model

Authors

Tharunika Sridhar

Abstract

Cloud-based solutions are increasingly demanding for efficient service provisioning with challenges such as spatially distributed sensors and actuators, stringent latency requirements, privacy concerns, and transportation of large data volumes. There is an emergence of a promising complement to traditional cloud computing called edge computing, which supports computation and storage near data generation sites. With the help of the proliferation of IoT, the advancements in Multi-Access Edge Computing (MEC), and 5G mobile communication, edge-integrated hybrid cloud systems have transformed into a robust ecosystem that unifies public and private cloud infrastructures within a unified management framework. This study explores the key roles of scalability and automation within edge-based hybrid cloud systems, notably their influence on enhancing efficiency, optimizing resource utilization, and workload distribution. An evidence-based descriptive analysis evaluates the improvement of these characteristics in information and network management, identifies the most critical areas for improving performance, and investigates associated problems and risks. NOMA-MEC models find promising applications in real-time implementations such as smart cities, industrial IoT, and vehicular networks. Such NOMA-MEC models facilitate adaptive resource scaling, task automation, and seamless connectivity over heterogeneous technologies like 5G and Wi-Fi. With the integration of ML and AI-driven algorithms, mobility-related and security-related issues also get addressed, thus increasing their practical applicability. The current research underlines the demand for a standardized hybrid edge-cloud framework to optimize the scaling and automation of sustainable, efficient, and future-ready networked environments.

Keywords

hybrid edge-cloud, multi-access hybrid, scalable cloud, AI cloud, heterogeneous cloud

Hybrid Cloud Edge Computing – An Analysis of Automation and Scalability as Features that Enhance the Model. Tharunika Sridhar. 2021. IJIRCT, Volume 7, Issue 5. Pages 1-11. https://www.ijirct.org/viewPaper.php?paperId=2412077