Geospatial ontology-based mission assignment in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been a focus for research in recent years. They enable data gathering across a wide range of domains and areas of interest from health service to environment monitoring, security, etc. Sensors are becoming cheaper, and as a result are being deployed in high density, at the same time; users’ requirements of the network are changing frequently, they can even exceed the capabilities of the sensors in the network sometimes. The network is expected to operate for a long period of time with many nodes operating on batteries. These challenges have raised the attention to the problem of mission assignment in WSNs. Mission assignment aims at allocating tasks to specific sensors in the network -according to their capabilities-to answer users requirements while at the same time preserving the energy of the network. This paper approaches the problem of mission assignment from a geospatial perspective: because sensors’ readings and data are associated with spatial properties of the sensors like their location and sensing range; spatial reasoning is an important aspect of mission assignment.

However, spatial reasoning is still very limited in WSNs and has not received much attention because of the lack of standardized modelling of space. In the center of our approach an integration of two ontologies; the W3C semantic sensor network ontology (SSN) which describes sensor nodes in the network and GeoSPARQL (the OGC standard for modelling and reasoning about spatial data). We present Geospatial Sensor Mission Assignment algorithm (GeoSMA); a branch and bound algorithm based on the spatial functions and relations between tasks’ and sensors’ spatial properties. The aim is to find the most appropriate set of nodes to answer various missions required by the users.

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