Scheduling Internet of Things tasks in cloud and fog computing environment using cuckoo search optimization
M. Santhosh Kumar, Ganesh Reddy Karri · 2024
Efficient task scheduling (TS) is essential for optimizing resource utilization and meeting quality of service (QoS) requirements in Internet of Things (IoT) deployments spanning cloud and fog computing (CFC) infrastructures. This chapter presents a novel approach utilizing the cuckoo search optimization algorithm (CSOA) for scheduling IoT tasks in such environments. The primary objective is to minimize task completion time while accommodating resource constraints and the dynamic nature of IoT networks. The CSOA is employed to effectively allocate tasks to suitable computing resources, considering factors such as processing capabilities, network latency, and data locality. Through extensive simulation experiments and comparative analyses with traditional scheduling algorithms, the efficacy of the proposed CSOA-based approach is evaluated. Results indicate significant improvements in task completion time by 28% and resource utilization by 36%, highlighting the effectiveness of the CSOA in addressing the complexities of IoT TS in CFC setups. Furthermore, the scalability and adaptability of the CSOA make it a promising candidate for real-world IoT applications, where efficient resource management is crucial for ensuring seamless operation and meeting user demands. Overall, this research contributes to the advancement of IoT TS techniques, offering insights into optimizing performance and resource utilization in CFC environments.