Reliability Optimization Scheduling and Energy Balancing for Real-Time Application in Fog Computing Environment.

Fog computing has the characteristics of stronger localized computing power and less data transmission load, thus better meeting the high energy efficiency, reliability, and real-time response requirements required by intelligent connected vehicle technology applications. Currently, research on fog computing task scheduling has become a hot topic, with existing research mainly focusing on low energy consumption or high real-time parallel task scheduling, which cannot meet the high reliability requirements in intelligent connected vehicle scenarios. Therefore, this paper establishes a fog computing task model based on Directed acyclic graph (DAG) to achieve accurate definition of energy, time and reliability. To achieve quantitative optimization of time and reliability indicators under energy constraints, a fog computing task scheduling algorithm was proposed and compared with existing scheduling algorithms. Then, the proposed algorithm is used to solve the DAG task list optimization problem based on fast Fourier transform (FFT) and Gaussian elimination (GE) structure. The experimental results show that compared with the existing ECLL method, ECLLRS has a more significant effect in satisfying the real-time and reliability of the system under the premise of limited energy budget.