CRSFTS: A Fault-Tolerant and Load-Balanced Scheduling Algorithm for Fog Computing

Fog computing bridges cloud infrastructure and IoT devices, enabling low-latency processing and efficient resource utilization. However, challenges such as node failures and load imbalances can degrade system reliability and performance. Existing scheduling approaches often lack integrated solutions for fault tolerance and load balancing. To address this, we propose the Cloud and Fog Computing System Fault Tolerance Scheduler (CRSFTS), which combines predictive fault detection, dynamic task migration, and adaptive load balancing. CRSFTS continuously monitors resource utilization and proactively mitigates failures [1]. Implemented using the iFogSim toolkit, CRSFTS outperforms traditional scheduling methods by improving task success rates by 20%, reducing latency by 15%, and optimizing energy consumption [2]. It also enhances system reliability and availability, offering a robust and scalable solution for fog computing environments.