Abstract
Edge computing has emerged as a transformative paradigm, bringing computation and data storage closer to the sources of data generation, thus addressing the limitations of traditional cloud architectures in latency-sensitive and resource-constrained environments. Kubernetes, as a leading container orchestration platform, has revolutionized the management of distributed applications in cloud settings. However, applying Kubernetes to edge computing introduces unique challenges, such as limited resources, intermittent network connectivity, stringent latency requirements, and heightened security risks. This paper investigates these challenges and explores innovative solutions for optimizing Kubernetes in edge computing scenarios. The study emphasizes the role of lightweight Kubernetes distributions, such as K3s and MicroK8s, in addressing resource constraints. It highlights edge-aware scheduling mechanisms and multi-cluster management frameworks like KubeEdge, which enable efficient workload placement across diverse environments. Networking advancements, including service meshes and integration with 5G technologies, are presented as critical enablers for low-latency and reliable communication at the edge. Furthermore, the paper examines the application of artificial intelligence (AI) and predictive analytics to enhance workload optimization, fault tolerance, and resource utilization. A comparative analysis illustrates significant improvements in performance metrics, such as reduced latency and optimized resource usage, achieved through these innovations. The paper also showcases real-world applications across industries, including healthcare, retail, manufacturing, and smart cities, demonstrating the transformative potential of Kubernetes in edge computing. This work aims to provide a comprehensive roadmap for researchers, developers, and industry practitioners seeking to leverage Kubernetes in edge environments. By addressing the inherent challenges and proposing cutting-edge solutions, the paper contributes to advancing the adoption of edge computing technologies, fostering a future where distributed systems can achieve unparalleled efficiency and scalability.
Citations
IRE Journals:
Naveen Kodakandla
"Optimizing Kubernetes for Edge Computing: Challenges and Innovative Solutions" Iconic Research And Engineering Journals Volume 4 Issue 10 2021 Page 210-221
IEEE:
Naveen Kodakandla
"Optimizing Kubernetes for Edge Computing: Challenges and Innovative Solutions" Iconic Research And Engineering Journals, 4(10)
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