Assume that the robot has 3 identical CPUs for executing the same algorithm which determines the next move out of the following 3 possible actions.
Show how you derive the probability ps that the entire system takes a correct action. Does the multiprocessor system improve the reliability in comparison with a single CPU?
--------------------------------------------------------------- Output Values | Majority | Correct? | Probability --------------------------------------------------------------- all 3 outputs are correct c c c | c | Y | p3 correct --------------------------------------------------------------- 2 outputs out of 3 outputs are correct c c w | c | Y | p2(1-p) correct c w c | c | Y | p2(1-p) correct w c c | c | Y | p2(1-p) correct --------------------------------------------------------------- only 1 out of 3 outputs is correct | 0 correct irrespective of which wrong outputs | --------------------------------------------------------------- all 3 outputs are wrong | 0 correct irrespective of which wrong outputs | ---------------------------------------------------------------The total probability of a correct output by 3 CPUs at the 1st trial is equal to p3 + 3p2(1-p) = p2(p + 3(1-p)) = p2(3 - 2p) = p2(1 + 2(1 - p)).
For p = 0.9 and 1-p = 0.1, the total probability of the correct output by 3 CPUs is 0.9 × 0.9 × (1 + 2 × 0.1) = 0.81 × 1.2 = 0.972. Thus, the multiprocessor system is 8% better than a single CPU.
For p = 0.999 and 1-p = 0.001, the total probability p_s of the correct output by 3 CPUs is 0.999 × 0.999 × (1 + 2 × 0.001) = 0.998001 × 1.002 = 0.999997002. Thus, the multiprocessor system is about 0.1% better than a single CPU.
Note that an improvement ratio decreasingly approaches toward 0 as p approaches 1.
However, such an improvement is not always achievable. We show more examples below.
Now, it is apparent that an improvement is possible only when p > 0.5 and the system reliability becomes worse than a single CPU when p < 0.5. The fact that an equilibrium occurs at p = 0.5 can analytically be derived by solving the following equation.
p = p2(1 + 2(1 - p))
Remark: You may consider that p < 0.5 is unrealistic. However, in extreme environments where there is lots of noise, very high or very low temperature, and high level of radiation, p is possibly low.