A framework for fault tolerance in distributed real time systems

Real time systems have a characteristic that they should be fault tolerant. In this paper, a fault tolerance mechanism for real time systems is proposed. First a model is discussed which is a modification of distributed recovery block and is based on distributed computing. Then a model is proposed which 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.