Reliability enhancement of real-time multiprocessor systems through dynamic reconfiguration

Enhancing the reliability of a system executing real-time jobs is, in many cases, one of the most important design goals. A dynamically reconfigurable system offers an approach for improvement of reliability. To achieve high reliability the most suitable recovery action must be used when a fault occurs, which means that some kind of optimal recovery strategy should be followed. This is called a dynamic recovery strategy. To satisfy the service requirements of real-time jobs with hard deadlines, a more powerful system, intuitively, should always be preferred. On the other hand, higher processing capacity means more processing modules and electronics parts, which may result in more frequent faults and a higher risk that the system will fail to complete the real-time jobs prior to their deadline. In this paper, we investigate the reliability enhancement of a real-time distributed computing system with hard deadlines through the employment of dynamic recovery strategies. Since the classical reliability evaluation technique is not applicable to a dynamically reconfigurable system, we present a new approach to reliability evaluation. The results show that the optimal recovery policy can significantly improve the system´s reliability, that both the job arrival rate and the job´s deadline have significant effect on the optimal reliability and optimal policy and that for a given workload and deadline, the maximum of the system reliability can be achieved at a certain (optimal) configuration