EGF-Tree: An Energy Efficient Index Tree for Facilitating Multi-region Query Aggregation in the Internet of Things

With the development of the Internet of Things, smart objects are used ubiquitously for supporting intelligent and cost-efficient applications. Techniques that collect and aggregate data from sensing devices are essential, and spatial index trees are usually constructed for facilitating the queries. Current spatial index trees are mostly not efficient for query data collection and aggregation. To address this challenge, we propose in this paper an Energy efficiency index tree (EGF-tree) for efficient data collection and aggregation, especially for the situation when sensor nodes are distributed unevenly. Generally, the region of the sensor network is divided evenly into grid cells. An EGF-tree is constructed through merging grid cells nearby. A multi-region query aggregation method is proposed for facilitating the collection and aggregation of simultaneous queries. Theoretical analysis and experiments show that our query aggregation technique is energy efficient.