Time Stamped Fault Tolerance in Real Time Systems

A wide application of real time systems is safety critical systems. These systems should be highly reliable. Fault tolerance is one of the approaches to achieve reliability. In this paper, a fault tolerance model for real time systems is proposed. This model incorporates the concept of time stamped fault tolerance. This model is based on distributed computing along with feed forward artificial neural network methodology. The proposed technique is based on execution of design diverse variants on replicated hardware, and assigning weights to the results produced by variants. Thus the proposed method encompasses both the forward and backward recovery mechanism, but main focus is on forward recovery. The main essence of the proposed technique is the inclusion of time for decision mechanism