An experimental study on geospatial indexing for sensor service discovery

• A scalable platform supporting large-scale sensor service discovery.
• A discovery approach more resilient to dynamicity of sensor services and environment.
• Accurate computation of the geographical features of gateways and sensor services.
• Superior performance over existing methods for response time and throughput.

The Internet of Things enables human beings to better interact with and understand their surrounding environments by extending computational capabilities to the physical world. A critical driving force behind this is the rapid development and wide deployment of wireless sensor networks, which continuously produce a large amount of real-world data for many application domains. Similar to many other large-scale distributed technologies, interoperability and scalability are the prominent and persistent challenges. The proposal of sensor-as-a-service aims to address these challenges; however, to our knowledge, there are no concrete implementations of techniques to support the idea, in particular, large-scale, distributed sensor service discovery. Based on the distinctive characteristics of the sensor services, we develop a scalable discovery architecture using geospatial indexing techniques and semantic service technologies. We perform extensive experimental studies to verify the performance of the proposed method and its applicability to large-scale, distributed sensor service discovery.