Fault-Tolerant Rate-Monotonic Scheduling

Due to the critical nature of the tasks in hard real-time systems, it is essential that faults be tolerated. In this paper, we present a scheme which can be used to tolerate faults during the execution of preemptive real-time tasks. We describe a recovery scheme which can be used to re-execute tasks in the event of single and multiple transient faults and discuss conditions that must be met by any such recovery scheme. We then extend the original Rate Monotonic Scheduling (RMS) scheme and the exact characterization of RMS to provide tolerance for single and multiple transient faults. We derive schedulability bounds for sets of real-time tasks given the desired level of fault tolerance for each task or subset of tasks. Finally, we analyze and compare those bounds with existing bounds for non-fault-tolerant and other variations of RMS.     

A nonpreemptive real-time scheduler with recovery from transient faults and its implementation

Real-time systems (RTS) are those whose correctness depends on satisfying the required functional as well as the required temporal properties. Due to the criticality of such systems, recovery from faults is an essential part of a RTS. In many systems, such as those supporting space applications, single event upsets (SEUs) are the prevalent type of faults; SEUs are transient faults and affect a single task at a time. We present a scheme to guarantee that the execution of real-time tasks can tolerate SEUs and intermittent faults assuming any queue-based scheduling technique. Three algorithms are presented to solve the problem of adding fault tolerance to a queue of real-time tasks by reserving sufficient slack in a schedule so that recovery can be carried out before the task deadline without compromising guarantees given to other tasks. The first algorithm is a dynamic programming optimal solution, the second is a linear-time heuristic for scheduling dynamic tasks, and the third algorithm comprises extensions to address queues with gaps between tasks (gaps are caused by precedence, resource, or timing constraints). We show through simulations that the heuristics closely approximate the optimal algorithm. Finally, we describe the implementation of the modified admission control algorithm, non-preemptive scheduler, and recovery mechanism in the FT-RT-Mach operating system.