Hybrid Overloading and Stochastic Analysis for Redundant Real-time Multiprocessor Systems

In multiprocessor systems, redundant scheduling is a technique that trades processing power for increased reliability. One approach, called primary-backup task scheduling, is often used in real-time multiprocessor systems to ensure that deadlines are met in spite of faults. Briefly, it consists in scheduling a secondary task conditionally, in such a way that the secondary task actually gets executed only if the primary task (or the processor executing it) fails to terminate properly. Doing so avoids wasting CPU resources in the failure-free case, but primary and secondary tasks must then compete for resources in case of failure. To overcome this, overloading strategies, such as primary and backup overloading (PB) and backup-backup overloading (BB), aim at improving schedulability while retaining a certain level of reliability. In this paper, we propose a hybrid overloading technique based on extended PB overloading, which combines advantages of both PB and BB overloading. The three overloading strategies are then compared through a stochastic analysis, and by simulating them under diverse system conditions. The analysis shows that hybrid overloading provides an excellent tradeoff between schedulability and reliability.