Data Intensive Mobile Sensor Networks (DIMSNs) introduce a promising but still under-utilized technology. Meanwhile, there is a growing confidence that certain applications (Killer Apps) have a potential to create a sustained market for this technology. For example, a large team of cooperative mobile robots can be considered as a wireless sensornet composed of a number of mobile nodes most of which are powerconstrained. Such mobile robots can be deployed in conjunction with stationary sensor nodes to acquire and process data for surveillance and tracking, environmental monitoring for highly sensitive areas, or execute search and rescue operations. This example illustrates conceptual attractiveness of the DIMSN systems that generates interesting and appealing research challenges (e.g., intelligent mobile agents, semantically enriched and contextaware wireless services, smart network monitoring infrastructures). However, while providing excellent funding opportunities, those challenges often underestimate the GRAND DETERRENTS that make moves towards practical data-intensive mobile sensornets extremely difficult.