Parallelizing itinerary-based KNN query processing in wireless sensor networks

Tao Yang Fu*, Wen-Chih Peng, Wang Chien Lee

*Corresponding author for this work

研究成果: Article同行評審

39 引文 斯高帕斯(Scopus)


Wireless sensor networks have been proposed for facilitating various monitoring applications (e.g., environmental monitoring and military surveillance) over a wide geographical region. In these applications, spatial queries that collect data from wireless sensor networks play an important role. One such query is the K-Nearest Neighbor (KNN) query that facilitates collection of sensor data samples based on a given query location and the number of samples specified (i.e., K). Recently, itinerary-based KNN query processing techniques, which propagate queries and collect data along a predetermined itinerary, have been developed. Prior studies demonstrate that itinerary-based KNN query processing algorithms are able to achieve better energy efficiency than other existing algorithms developed upon tree-based network infrastructures. However, how to derive itineraries for KNN query based on different performance requirements remains a challenging problem. In this paper, we propose a Parallel Concentric-circle Itinerary-based KNN (PCIKNN) query processing technique that derives different itineraries by optimizing either query latency or energy consumption. The performance of PCIKNN is analyzed mathematically and evaluated through extensive experiments. Experimental results show that PCIKNN outperforms the state-of-the-art techniques.

頁(從 - 到)711-729
期刊IEEE Transactions on Knowledge and Data Engineering
出版狀態Published - 19 三月 2010

指紋 深入研究「Parallelizing itinerary-based KNN query processing in wireless sensor networks」主題。共同形成了獨特的指紋。