An Adaptive Simulated Annealing Algorithm for Optimizing Task Scheduling in Internet of Things

The Internet of Things (IoT) has grown significantly, and hence, it is being used extensively in real-time applications. However, this exponential data growth has also brought issues like CPU scheduling delays and increased computational overhead. Traditional CPU scheduling algorithms optimize one factor leading to delays, like task scheduling or execution time. In practice, delays occur because of a mix of both task scheduling and execution time. To overcome this weakness, this paper proposes an adaptive cooling rate simulated annealing algorithm to optimize scheduling time and execution times for effectively addressing scheduling delay problems. Simulation outcomes show that the proposed algorithm outperforms current methods in minimizing scheduling delays.