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Today's mobile computing environments aggregate many entities, all of them with a number of internal sensors, processing applications and other, user given information that can be shared with others over the available networks. Tomorrow's ubiquitous computing environments, where the number of sensors is assumed to be even significantly higher, face the challenge that information exchange between entities has to be controlled, not only to protect privacy and to unburden the wireless networks - but also to reduce load on the receiving entities that have to process all incoming information. The approach we propose in this work measures the importance of some information and the interest of the receiver in it, before it is transferred. We apply it in two scenarios with limited resources. In vehicle-to-vehicle communications the transmission time while cars meet and bandwidth availability of the wireless channel is the critical resource, forcing to reduce information exchange. In context inference on mobile devices processing power and battery life are limited and responsiveness to user actions is most important. Hence only the most important information should be processed.