An energy efficient hierarchical clustering index tree for facilitating time-correlated region queries in wireless sensor network

In the Internet of Things, smart things communicate with each other, and sensed data are aggregated and queried for satisfying certain requests of end-users. When a region of interest requires to be monitored continuously, the strategy that each query is to be executed independently through gathering sensed data of target sub-regions may not be energy efficient, since the values of sensors may have no significant difference in proximate sensing time-slot in some applications. To mitigate the energy consumption in this context, in this paper we propose an energy-efficiency hierarchical clustering index tree for organizing these grid cells. Then, we develop a time-correlated region query technique for answering continuous queries. Theoretical analysis show that our technique is energy efficient compared with traditional techniques.