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.

Group communication is a widely studied paradigm for building fault-tolerant distributed systems. The Armada project at the University of Michigan is a collaborative effort with the Honeywell Technology Center to study how real-world applications use group communication. We describe the results of our experience implementing a fault-tolerant distributed radar tracking system, and discuss how we were able to simplify our design and implementation by utilizing additional services built on top of the group communication model.

Real time systems are being increasingly used in several applications which are time critical in nature. Fault tolerance is an important requirement of such systems, due to the catastrophic consequences of not tolerating faults. We study a scheme that provides fault tolerance through scheduling in real time multiprocessor systems. We schedule multiple copies of dynamic, aperiodic, nonpreemptive tasks in the system, and use two techniques that we call deallocation and overloading to achieve high acceptance ratio (percentage of arriving tasks scheduled by the system). The paper compares the performance of our scheme with that of other fault tolerant scheduling schemes, and determines how much each of deallocation and overloading affects the acceptance ratio of tasks. The paper also provides a technique that can help real time system designers determine the number of processors required to provide fault tolerance in dynamic systems. Lastly, a formal model is developed for the analysis of systems with uniform tasks.

We present a scheme to guarantee that the execution of real-time tasks can tolerate transient and intermittent faults assuming any queue-based scheduling technique. The scheme is based on reserving sufficient slack: in a schedule such that a task can be re-executed before its deadline without compromising guarantees given to other tasks. Only enough slack is reserved in the schedule to guarantee fault tolerance if at most one fault occurs within a time interval. This results in increased schedulability and a very low percentage of deadline misses even if no restriction is placed on the fault separation. We provide two algorithms to solve the problem of adding fault tolerance to a queue of real-time tasks. The first is a dynamic programming optimal solution and the second is a greedy heuristic which closely approximates the optimal.