Supporting Situation-Aware services with Virtual Macro Sensors

Next-generation communication services will be required to adapt their behavior to the specific characteristics of the physical and social environment in which they will be invoked. The technology to acquire contextual information will be increasingly available, e.g., in the form of highly-pervasive sensor networks infrastructure. Indeed, such infrastructure can lead to the production of overwhelming amounts of information, difficult to be managed and interpreted by services. This calls for proper solutions to enable services to extract meaningful general-purpose data from distributed sensors in a compact way. The approach presented in this paper relies on a simple algorithm to let a sensor network self-organize a virtual partitioning in correspondence of spatial regions characterized by similar sensing patterns, and to let distributed aggregation of sensorial data take place on a perregion basis. This makes it possible for services to gather information about the surrounding world as if it was generated by a limited number of virtual macro sensors, independently of the actual structure and density of the underlying sensing infrastructure.