Synchronization of Intelligence, Surveillance, and Reconnaissance (ISR) activities to maximize the utilization of limited resources (both in terms of quantity and capability) has become critically important to military forces. In centralized frameworks, a single node is responsible for determining and disseminating decisions (e.g., tasks assignments) to all nodes in the network. This requires a robust and reliable communication network. In decentralized frameworks, processing of information and decision making occur at different nodes in the network, reducing the communication requirements. This research studies the degradation of solution quality (i.e., potential information gain) as a centralized system synchronizing ISR activities moves to a decentralized framework. The mathematical programming model of previous work1 has been extended for multi-perspective optimization in which each collection asset develops its own decisions to support mission objectives based only on its perspective of the environment. Different communication strategy are considered. Collection assets are part of the same communication network (i.e., a connected component) if: (1) a fully connected network exists between the assets in the connected component, or (2) a path (consisting of one or more communication links) between every asset in the connected component exists. Multiple connected components may exist among the available collection assets supporting a mission. Information is only exchanged when assets are part of the same network. The potential location of assets that are not part of a connected component can be considered (with a suitable decay factor as a function of time) as part of the optimization model.