  Network reliability measures the probability that a target node is reachable
from a source node in an uncertain graph, i.e., a graph where every edge is
associated with a probability of existence. In this paper, we investigate the
novel and fundamental problem of adding a small number of edges in the
uncertain network for maximizing the reliability between a given pair of nodes.
We study the NP-hardness and the approximation hardness of our problem, and
design effective, scalable solutions. Furthermore, we consider extended
versions of our problem (e.g., multiple source and target nodes can be provided
as input) to support and demonstrate a wider family of queries and
applications, including sensor network reliability maximization and social
influence maximization. Experimental results validate the effectiveness and
efficiency of the proposed algorithms.
