A fault-tolerant scheduling algorithm that minimizes the number of replicas in heterogeneous service-oriented cloud computing systems

The service-oriented heterogeneous cloud computing system offers paid computing services through its powerful processors. However, task execution failures caused by processors can diminish application reliability and user service quality. Replication technology can enhance application reliability, but an inappropriate number of replicas may occupy valuable computing resources. To address this, we propose FastMinRR, a fault-tolerant scheduling algorithm that rapidly minimizes the number of replicas while meeting reliability requirements. FastMinRR initially allocates all tasks to the currently available and most reliable processor without replication, utilizing a priority queue to store tasks based on increasing reliability. Subsequently, FastMinRR dequeues a task, increases its replicas, updates reliability, recalculates application reliability, and enqueues the task. This process repeats until the application reliability aligns with requirements. Experiments demonstrate that, compared to existing fault-tolerant scheduling algorithms in service-oriented heterogeneous cloud computing systems, FastMinRR efficiently increases the minimum number of task replicas and meets application reliability requirements.