Article
Smart Service Embedding in Heterogeneous IoT Networks: A Real-Time Energy Optimization Framework
This work proposes an energy-efficient service embedding framework for heterogeneous IoT networks that overcomes challenges with state-of-the-art techniques that do not account for energy constraints. By using real-time energy feedback and an optimization algorithm for placement, the framework dynamically appends services based on node energy, processing capacity, and latency. Simulation for 50 service requests reduces energy by 40.7% from 75.9 J to 45.0 J. Furthermore, node longevity also improved with 39 active nodes after 5 hrs of execution, whereas the baseline had 18. Average service latency decreased from 280 ms to 190 ms with low latency in addition to energy savings. The framework improves quality of service and sustainability for dynamic IoT networks and suits real-time applications such as smart cities and healthcare. Future work includes mobility-aware service placement, predictive modeling, and the incorporation of blockchain for secure deployment.
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