Abstract
Data collection is an important application of wireless sensor networks (WSNs) and Internet of Things (IoT). Current routing and addressing operations in WSNs are based on IP addresses, while data collection and data queries are normally information-centric. The current IP-based approach incurs significant management overheads and is inefficient for semantic data collection and queries. To address the above issue, this paper proposes a semantic data collection tree (sDCT) construction scheme to build up a semantic data collection tree for wireless sensor networks. The semantic tree is rooted at the edge/sink and supports data collection tasks, queries, and configurations efficiently. We implement the sDCT in Contiki and evaluate the performance of the sDCT in comparison with the state-of-the-art scheme, 6LoWPAN/RPL and L2RMR, using telosb sensors under various scenarios. The obtained results show that the sDCT achieves a significant improvement in terms of the energy efficiency and the packet transmissions required for data collection or a query task compared to 6LoWPAN/RPL and L2RMR.
Highlights
Data collection and data queries are important applications in wireless sensor networks (WSNs) and Internet of Things (IoT)
For the same purpose of supporting semantic data collection and data queries, this paper proposes a semantic data collection tree construction scheme for the edge to build up a semantic data collection tree for wireless sensor networks based on information-centric networking [4,9,10,11]
The obtained results show that the semantic data collection tree (sDCT) achieves a significant improvement in terms of the energy efficiency and the packet transmissions required for data collection or a query task compared to IP-based data collection tree (ipDCT) and L2RMR [12]
Summary
Data collection and data queries are important applications in wireless sensor networks (WSNs) and Internet of Things (IoT). The mismatching between the user semantic query model and the data collection tree building approach incurs complicated processes required for resource-constrained sensor nodes at both the network layer and the application layer. Each node receives DIO messages with DODAG configuration information to configure themselves and selects parent nodes based on the ranking to be reachable from the DODAG root By this way, the DAG is constructed for MP2P traffic flows. For the same purpose of supporting semantic data collection and data queries, this paper proposes a semantic data collection tree construction scheme for the edge to build up a semantic data collection tree (sDCT) for wireless sensor networks based on information-centric networking [4,9,10,11]. The proposed semantic data collection tree (sDCT) supports common traffic patterns in WSNs natively without requiring route lookup or completed route information. The obtained results show that the sDCT achieves a significant improvement in terms of the energy efficiency and the packet transmissions required for data collection or a query task compared to ipDCT and L2RMR [12]
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