  This paper regards the problem of optimally placing unreliable sensors in a
one-dimensional environment. We assume that sensors can fail with a certain
probability and we minimize the expected maximum distance from any point in the
environment to the closest active sensor. We provide a computational method to
find the optimal placement and we estimate the relative quality of equispaced
and random placements. We prove that the former is asymptotically equivalent to
the optimal placement when the number of sensors goes to infinity, with a cost
ratio converging to 1, while the cost of the latter remains strictly larger.
