  We study how we can accelerate the spreading of information in temporal
graphs via delaying operations; a problem that captures real-world applications
varying from information flows to distribution schedules. In a temporal graph
there is a set of fixed vertices and the available connections between them
change over time in a predefined manner. We observe that, in some cases, the
delay of some connections can in fact decrease the time required to reach from
some vertex (source) to another vertex (target). We study how we can minimize
the maximum time a set of source vertices needs to reach every other vertex of
the graph when we are allowed to delay some of the connections of the graph.
For one source, we prove that the problem is W[2]-hard and NP-hard, when
parameterized by the number of allowed delays. On the other hand, we derive a
polynomial-time algorithm for one source and unbounded number of delays. This
is the best we can hope for; we show that the problem becomes NP-hard when
there are two sources and the number of delays is not bounded. We complement
our negative result by providing an FPT algorithm parameterized by the
treewidth of the graph plus the lifetime of the optimal solution. Finally, we
provide polynomial-time algorithms for several classes of graphs.
