A New Semantic-based Query Processing Architecture

With rapid development of sensor networks technology, it becomes feasible to deploy multiple sensor networks in relevant area to collect interested information. Sensor nodes belonging to different sensor networks may not be able to collaborate properly to gain the capacity or performance due to inability to exchange information with each other. In this paper we propose a semantic-based query processing architecture that enables in-network processing of multiple sensor networks with unified protocol. In this architecture, there are low-level semantics in raw sensory data which are the mapping of the physical world. Semantics will be attached to the data to make the sensory data be understood more easily. In the process of matching, aggregated data are generated and semantics are attached to the aggregated data. The advantage of semantic-based architecture is that it can solve the problems in more complex situations. It makes the exchange of sensory data in multiple sensor networks possible and efficiently. The process of semantic creation and maintenance is described. We also introduce the concept of semantic data model. This infrastructure enables efficient information exchange and information extraction among multiple sensor networks.