We revisit the moving k nearest neighbor (MkNN) query, which computes one's knearest neighbor set and maintains it while at move. Existing MkNN algorithmsare mostly safe region based, which lack efficiency due to either computingsmall safe regions with a high recomputation frequency or computing larger saferegions but with a high cost for each computation. In this demonstration, weshowcase a system named INSQ that adopts a novel algorithm called theInfluential Neighbor Set (INS) algorithm to process the MkNN query in bothtwo-dimensional Euclidean space and road networks. This algorithm uses a smallset of safe guarding objects instead of safe regions. As long as the thecurrent k nearest neighbors are closer to the query object than the safeguarding objects are, the current k nearest neighbors stay valid and norecomputation is required. Meanwhile, the region defined by the safe guardingobjects is the largest possible safe region. This means that the recomputationfrequency is also minimized and hence, the INS algorithm achieves high overallquery processing efficiency.
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