  We examine the problem of optimal design in the context of filtering multiple
random walks. Specifically, we define the steady state E-optimal design
criterion and show that the underlying optimization problem leads to a second
order cone program. The developed methodology is applied to tracking network
flow volumes using sampled data, where the design variable corresponds to
controlling the sampling rate. The optimal design is numerically compared to a
myopic and a naive strategy. Finally, we relate our work to the general problem
of steady state optimal design for state space models.
