KubeEdge for Scalable IoT Applications

The rise of IoT (Internet of Things) presents both opportunities and challenges in managing large-scale deployments. Traditional cloud solutions struggle with realtime data processing and scalability for numerous connected devices. KubeEdge, an extension of Kubernetes, addresses these challenges by extending cloud-native orchestration to the edge of the network. This paper explores how KubeEdge enhances IoT applications through efficient edge computing, crucial for reducing latency and optimizing resource utilization. KubeEdge extends Kubernetes’ capabilities to manage containerized applications on edge nodes, enabling localized data processing and reducing reliance on centralized cloud infrastructures. This approach minimizes latency and lowers bandwidth costs, making it ideal for real-time, data-intensive IoT applications. This research paper highlights practical use cases and proposes strategic deployment frameworks, emphasizing KubeEdge’s benefits in scalability, resource management, and operational efficiency. It also addresses potential challenges in deploying KubeEdge at scale, such as managing resource distribution and integrating with existing infrastructure. This paper provides actionable insights and best practices for Utilizing KubeEdge in various IoT contexts, demonstrating its impact on improving the performance and scalability of IoT systems.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/ic3i61595.2024.10828876
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
0.70
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KubeEdge for Scalable IoT Applications

Prerna Ajmani, Lalit Mohan Saini, V Asha, N R G Sreevani et al.
2 citations
IoT and Edge/Fog Computing
0.70
article

KubeEdge for Scalable IoT Applications

Prerna Ajmani, Lalit Mohan Saini, V Asha, N R G Sreevani, Khobragade Pithamber
article en
2 citations

Abstract

The rise of IoT (Internet of Things) presents both opportunities and challenges in managing large-scale deployments. Traditional cloud solutions struggle with realtime data processing and scalability for numerous connected devices. KubeEdge, an extension of Kubernetes, addresses these challenges by extending cloud-native orchestration to the edge of the network. This paper explores how KubeEdge enhances IoT applications through efficient edge computing, crucial for reducing latency and optimizing resource utilization. KubeEdge extends Kubernetes’ capabilities to manage containerized applications on edge nodes, enabling localized data processing and reducing reliance on centralized cloud infrastructures. This approach minimizes latency and lowers bandwidth costs, making it ideal for real-time, data-intensive IoT applications. This research paper highlights practical use cases and proposes strategic deployment frameworks, emphasizing KubeEdge’s benefits in scalability, resource management, and operational efficiency. It also addresses potential challenges in deploying KubeEdge at scale, such as managing resource distribution and integrating with existing infrastructure. This paper provides actionable insights and best practices for Utilizing KubeEdge in various IoT contexts, demonstrating its impact on improving the performance and scalability of IoT systems.

Guru Gobind Singh Indraprastha University (IN), Aeronautical Development Agency (IN)
Affordable and clean energy
Openalex Percentile: Top 25%
IoT and Edge/Fog Computing
0.70
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