Monitoring large-scale networks is a critical yet challenging task. Enormous number of nodes and links, limited power, and lack of direct access to the entire network are the most important difficulties. In applications such as network routing, where all nodes need to monitor the status of the entire network, the situation is even worse. In this letter, a collaborative model in which nodes pick up information from measurements generated by other nodes is proposed. Using this model, for the first time, an upper bound is derived for the number of measurements that each node must generate, such that the expected number of measurements observed by each node is sufficient to provide a global view of the entire networked data. Finally, by using this upper bound, an efficient optimization method is introduced to minimize the total number of measurements. The feasibility and accuracy of the proposed method is verified through extensive numerical simulations.