Delay-aware heterogeneous cluster-based data acquisition in Internet of Things. (January 2018) - Ramachandran, Nandhakumar; Perumal, Varalakshmi
Abstract: The environmental conditions of a wildlife habitat are monitored using many heterogeneous sensors, including temperature, humidity, pressure, and water-level sensors. Sensor data are collected from various regions for knowledge retrieval about the various parameters to analyse the wildlife habitat and take necessary actions. The Delay-Aware Heterogeneous Cluster-based Data Acquisition (DA-HCDA) technique is proposed, which ensures maximum coverage. A multifarious Sensor-based Cluster Formation Algorithm (MSCFA) is used to from the cluster and elect the controllers to handle the different types of sensors. A multi-tier aggregation function called Quartile Aggregation is proposed, which eliminates the redundancy of aggregated data at the controller. Thus, the proposed DA-HCDA and Quartile Aggregation mechanism improve the network lifetime and end-to-end delay across the wildlife habitat reserve.