An Efficient Fault-tolerant Scheduling Algorithm for Periodic Real-time Tasks in Heterogeneous Platforms

Fault-tolerant real-time scheduling algorithm is one of the most important means to ensure the timeliness and high availability characteristics of fault-tolerant real-time systems. Existing scheduling models for periodic real-time task in heterogeneous platforms typically require the number of processors in the systems to be determined in advance; hence prohibit the scalability and the performance of distributed systems. The algorithms based on these models also require a large number of schedubility tests which lead to long execution time. To address these problems, we propose a primary and backup replica partition based fault-tolerant scheduling algorithm (PBPFT) based on a scalable scheduling model using heterogeneity that does not have to determine the scale of the distributed system in advance. The PBPFT approach also takes advantage of backup copy overlapping and phasing delay techniques to minimize system redundancy, and adopts the processor grouping technique to simplify algorithm complexity. Comprehensive experiments are conducted, and the results validate high resource utilization and commendable performance of our proposed approach.