I study several graph problems in which the information of the given graphs are incomplete. I devise randomized algorithms to solve those problems and provide theoretical analysis for their performances. In the rumor spreading problem, a connected graph with n nodes is given and the objective is to spread a rumor, which is initiated by one node, to all nodes in the graph as fast as possible under distributed communication. I extend the classic PUSH-PULL protocol to stream B rumors in a graph from a single source node to all nodes in the graph and show that perfect pipelining can be achieved with high probability in directed random graphs and PA-graphs. Motivated by online advertisement and exchange settings, the oblivious matching pro...