Novel itinerary-based KNN query algorithm leveraging grid division routing in wireless sensor networks of skewness distribution

Wireless sensor networks (WSN) is a key enabling technique for achieving the vision of the Internet of Things. In many applications of WSN such as environmental monitoring and vehicle tracking, they may require to launch spatial queries for collecting and gathering sensory data for achieving certain goals. One such query is the nearest neighbor (KNN) query, which aims to collect sensory data from sensor nodes nearest to a certain query location. Techniques, namely the itinerary-based KNN query algorithms, are recently developed for facilitating KNN queries. Generally, these techniques propagate queries and collect data along a predetermined itinerary. However, query accuracy and boundary expansion are two challenges that are not well addressed. To mitigate these issues, in this paper, we propose a novel KNN query algorithm based on grid division routing in the setting of skewness distribution, where the itinerary is formed based on the connectivity of adjacent grid cells centers. This technique can achieve better query accuracy and cause less energy consumption by executing the query concurrently in subregions. Besides, the void region problem is well addressed based on the proximity of neighbor grid cells. Experiment result shows that our technique performs better in several aspects including query accuracy, data redundancy, and energy efficiency.