IDST-CNM: Internet of Deep Sea Things using Cloudlet and NFV as network infrastructure for Monitoring

Underwater disasters, particularly oil and gas leaks, pose significant threats to marine ecosystems. Early detection and rapid response are crucial for effective mitigation. This paper introduces IDST-CNM, an energy-efficient network architecture leveraging Cloudlet computing and Network Function Virtualization (NFV) for monitoring the Internet of Deep-Sea Things (IoDST). IDST-CNM is specifically designed for early warning systems that detect oil or gas leaks on the ocean floor. This architecture minimizes energy consumption using intelligent data forwarding paths, Cloudlet computing for localized data processing, NFV for dynamic resource allocation, and queueing theory with stochastic processing for performance optimization. The proposed architecture offers unprecedented flexibility and adaptability, addressing the critical need for proactive oil and gas pollution monitoring on the ocean floor. Simulation results demonstrate that IDST-CNM achieves a superior balance between throughput, energy efficiency, packet delivery ratio, and network lifetime compared to existing IoDST approaches. Specifically, IDST-CNM maintains higher network longevity and significantly lower end-to-end delays, indicating its suitability for time-critical applications like early disaster warning in deep-sea environments. This work presents a significant advancement towards robust, energy-conscious deep-sea monitoring solutions.