  This paper aims to provide a new perspective on the interplay between
decentralization -- a prevalent character of multi-agent systems -- and
centralization, i.e., the task of imposing central control to meet system-level
goals. In particular, in the context of networked opinion dynamic model, the
paper proposes and discusses a framework for centralization. More precisely, a
decentralized network consists of autonomous agents and their social structure
that is unknown and dynamic. Centralization is a process of appointing agents
in the network to act as access units who provide information and exert
influence over their local surroundings. We discuss centralization for the
DeGroot model of opinion dynamics, aiming to enforce opinion convergence using
the minimum number of access units. We show that the key to the centralization
process lies in selecting access units so that they form a dominating set. We
then propose algorithms under a new local algorithmic framework, namely
prowling, to accomplish this task. To validate our algorithm, we perform
systematic experiments over both real-world and synthetic networks and verify
that our algorithm outperforms benchmarks.
