  In the Dynamic Resource Allocation (DRA) problem, an administrator has to
allocate a limited amount of resources to the nodes of a network in order to
reduce a diffusion process (DP) (e.g. an epidemic). In this paper we propose a
multi-round dynamic control framework, which we realize through two derived
models: the Restricted and the Sequential DRA (RDRA, SDRA), that allows for
restricted information and access to the entire network, contrary to standard
full-information and full-access DRA models. At each intervention round, the
administrator has only access -- simultaneous for the former, sequential for
the latter -- to a fraction of the network nodes. This sequential aspect in the
decision process offers a completely new perspective to the dynamic DP control,
making this work the first to cast the dynamic control problem as a series of
sequential selection problems. Through in-depth SIS epidemic simulations we
compare the performance of our multi-round approach with other resource
allocation strategies and several sequential selection algorithms on both
generated, and real-data networks. The results provide evidence about the
efficiency and applicability of the proposed framework for real-life problems.
