Proactive Fault-tolerance Driven Task Scheduling System for IoV Edge Networks

The emergence of Internet of Vehicles (IoV) technology provides a wider range of application scenarios for edge computing based on Vehicle-to-everything (V2X). It is essential to ensure the high availability and reliability of services in IoV systems. Currently, cloud service providers have established a data center level of fault tolerance, such as redundancy and checkpoints, guaranteeing the reliability of cloud infrastructure and reducing phenomena such as service termination or downtime. However, current computing systems reactively handle failures. Especially in edge computing, this approach not only lacks flexibility but also consumes excessive system resources, which is not conducive to ensuring the reliability in resource-constrained systems and poses security risks to end users. To mitigate this problem, we propose a Proactive Fault-tolerance Driven Task Scheduling System. Different from the traditional reactive strategies, the proposed framework predicts the possible system crashes by monitoring the critical state indicators of the computing system. According to the prediction results, a class of tasks or services that are most likely to be terminated are rescheduled in advance. Extensive experiments are conducted, and evaluation results demonstrate that our proposed proactive fault tolerance framework can effectively improve the long-term performance of the IoV edge system.