K Nearest Neighbour Query Processing in Wireless Sensor and Robot Networks

In wireless sensor and robot networks (WSRNs), static sensors report event information to one of robots. In the k nearest neighbour query processing problem in WSRN, robot receiving event report needs to find k nearest robots (KNN) to react to the event, among those connected to it. In this article, we propose a new method to estimate a search boundary, which is a circle centred at query point. Two algorithms are presented to disseminate the message to robots of interest and aggregate their data (e. g. the distance to query point). Multiple Auction Aggregation (MAA) is an algorithm based on auction protocol, with multiple copies of query message being disseminated into the network to get the best bidding from each robot. Partial Depth First Search (PDFS) algorithm attempts to traverse all the robots of interest with a query message to gather the data by depth first search. In this article, we also optimize a traditional itinerary-based KNN query processing method called IKNN and compare it with our proposed algorithms. The experimental results indicate that the overall performance of MAA outweighs IKNN.