Dynamic Scheduling and Optimal Resource Allocation Model for Cloud-Based IoT Applications

This paper presents a dynamic model of scheduling and resource allocation that is custom-fit for cloud-based IoTapplications. Our proposed model addresses the specific challenges associated with fluctuating workload demands,all arising from the IoT applications, through predictive analytics to forecast resource needs, adaptive scheduling fordynamic resource allocation, and energy-aware mechanisms aimed at optimizing power usage. Simulation resultsshow that the proposed model significantly outperforms conventional static and semi-dynamic models with up to۳۰% reductions in latency and energy consumption. It improves resource utilization, reduces response time, andhence increases throughput; therefore, it is proved suitable for IoT real-time applications. This paper, therefore,provides an efficient and scalable technique of cloud resource management in dynamic IoT environments like smartcities, health systems, and industrial IoT systems.

کلیدواژه ها:

IoT ، Cloud Computing ، Dynamic Scheduling ، Resource Allocation ، Predictive Analytics