Securing and Sustaining IoT Edge-Computing Architectures Through Nanoservice Integration

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Abstract
The rapid proliferation of the Internet of Things (IoT) and edge computing devices calls for solutions that deliver low latency, energy efficiency, and robust security-often challenging goals to balance simultaneously. This paper introduces a novel nanoservice-based framework that dynamically adapts to changing demands while achieving sustainable and secure edge operations. By breaking down functionalities into specialized and narrowly scoped nanoservices that are requested only as needed and eliminated when idle, the approach significantly reduces latency and energy usage compared to conventional, more static methods. Moreover, integrating a Zero-Trust Architecture (ZTA) ensures that every component-computational or security-related-is continuously verified and restricted through strict access controls and micro-segmentation. This framework's adaptability extends uniformly to all nanoservices, including those providing security features, thereby maintaining strong protective measures even as workloads and network conditions evolve. Experimental evaluations on IoT devices under varying workloads demonstrate that the proposed approach significantly reduces energy consumption and latency while maintaining security and scalability. These results underscore the potential for an integrated, flexible model that simultaneously addresses energy efficiency, performance, and security-an essential trifecta in future edge computing environments.
Funding Information
  • Finnish Doctoral Program Network in Artificial Intelligence (VN/3137/2024-OKM-6)

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