Abstract
In many spatial applications, users are only interested in data objects that are visible to them. Hence, finding visible data objects is an important operation in these real-world spatial applications. This study addressed a new type of spatial query, the View field-aware Visible k Nearest Neighbor (V2-kNN) query. Given the location of a user and his/her view field, a V2-kNN query finds data object p so that p is the nearest neighbor of and visible to the user, where visible means the data object is (1) not hidden by obstacles and (2) inside the view field of the user. Previous works on visible NN queries considered only one of these two factors, but not both. To the best of our knowledge, this work is the first to consider both the effect of obstacles and the restriction of the view field in finding the solutions. To support efficient processing of V2-kNN queries, a grid structure is used to index data objects and obstacles. Pruning heuristics are also designed so that only data objects and obstacles relevant to the final query result are accessed. A comprehensive experimental evaluation using both real and synthetic datasets is performed to verify the effectiveness of the proposed algorithms.
Highlights
The k nearest neighbor query is an important spatial query type that has been studied extensively during the past decade [1,2]
We proposed algorithms for processing V2-k nearest neighbor (kNN) queries, which retrieve k visible data objects in the presence of obstacles within user’s view field
Two factors affect the visibility of data objects: (1) the view field and (2) physical obstacles
Summary
The k nearest neighbor (kNN) query is an important spatial query type that has been studied extensively during the past decade [1,2]. Conventional kNN query processing algorithms are inefficient for supporting current real-world applications as they do not take the visibility of data objects into consideration. This issue is illustrated, where q is the query point, O = {o1, o2} are the obstacles (denoted by straight lines), and P = {p1, p2, p3, p4, p5} is a set of data objects. If every data object p is accessed and compared with all the obstacles to determine whether p is inside the given view field, the I/O cost, as well as the computation time must be extremely high To address this problem, we propose an efficient algorithm to retrieve the visible data objects in a given view field. Note that as we have mentioned in the previous section, none of these works consider the effect of obstacles and the view field at the same time
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