An optimal parallel average voting for fault-tolerant control systems

Fault-tolerant systems are such systems that can continue their operation, even in presence of faults. Redundancy as one of the main techniques in implementation of fault-tolerant control systems uses voting algorithms to choose the most appropriate value among multiple redundant and probably faulty results. Average (mean) voter is one of the commonest voting methods which is suitable for decision making in highly-available and long-missions applications in which the availability and speed of the system is critical. In this paper, we introduce a new generation of average voter based on parallel algorithms. Since parallel algorithms normally have high processing speed and are especially appropriate for large scale systems, we have used them to achieve an optimal parallel average voting algorithm with a time complexity of O (log n) with n/log n equations processors on EREW shared-memory for applications where the size of input space is large.