Information discovery in mission-critical wireless sensor networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Duty cycle aware spatial query processing in wireless sensor networks
Computer Communications
Searching K-nearest neighbor nodes based on node density in ad hoc networks
Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia
SMashQ: spatial mashup framework for k-NN queries in time-dependent road networks
Distributed and Parallel Databases
Spatial query processing in wireless sensor networks - A survey
Information Fusion
| Hi-index | 0.00 |
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.