We study the problem of optimal leader selection in consensus networks under two performance measures: 1) formation coherence when subject to additive perturbations, as quantified by the steady-state variance of the deviation from the desired trajectory, and 2) convergence rate to a consensus value. The objective is to identify the set of k leaders that optimizes the chosen performance measure. In both cases, an optimal leader set can be found by an exhaustive search over all possible leader sets; however, this approach is not scalable to large networks. In recent years, several works have proposed approximation algorithms to the k-leader selection problem, yet the question of whether there exists an efficient, noncombinatorial method to identify the optimal leader set remains open. This work takes a first step toward answering this question. We show that, in 1-D weighted graphs, namely, path graphs and ring graphs, the k-leader selection problem can be solved in polynomial time (ink and the network size n). We give an O(n 3 ) solution for optimal k-leader selection in path graphs and an O(kn 3 ) solution for optimal k-leader selection in ring graphs.
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Patterson et al. (2016) studied this question.
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