In-network processing of spatial queries is a data collection technique that is widely used in wireless sensor networks (WSN). The user generates sql-like query specifying the kind of information (e.g., temperature, humidity, etc.), duration of measurement, periodicity, kind of data aggregation (Max, Min, average, etc.), and region of interest, etc. The generated queries are routed to the nodes belonging to the specific region of interest, mainly using standard WSN geographic routing algorithms. With the advent of Internet of Things (IoT), the Internet Engineering Task Force (IETF) defined a standard routing algorithm to IoT enabled wireless sensor networks, so called RPL. The latter builds a tree like routing topology that is inefficient for spatial type of queries, because it floods the message to all nodes either inside or outside the target region. In a previous research, we have introduced a performance enhanced routing algorithm, we refer as PA-RPL (Partition Aware-RPL), that considers the importance of partition (or region). In this work, we propose an extension to this PA-RPL algorithm, enabling appropriate/efficient routing of spatial queries in an IoT enabled wireless sensor network. Our results demonstrate: (i) a high scalability for large size and density networks, (ii) dramatic reduction in transferred query messages that alleviates the bandwidth bottleneck, and a (iii) 20% energy gain, in contrast to standard RPL.
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