Proposed fog-cloud hybrid model improves task offloading and scheduling in IoT for intelligent transportation systems, indicating enhanced performance.
Key Points
The proposed model reduced task delays by up to 28.4% and energy usage by about 31.6%, enhancing overall efficiency.
Using the analytical hierarchy process, tasks were prioritized as delay sensitive or computation intensive, optimizing resource allocation.
The framework includes a fault tolerance mechanism to monitor task execution and assign backup nodes during failures.
Extensive simulations with OMNeT++ demonstrated improved success rates of tasks under heavy loads by 9–12%.