Florida International University

Mingjin Zhang

Tao Li

Naphtali David Rishe

Jahkell Lazarre

Weitong Liu

Devices and methods for providing Voronoi diagram-based progressive continuous range query (CRQ) computation for location-based services are provided. A method can include indexing all interest points using a Voronoi R-tree data structure in a server-side computing device. When a client mobile device sends a CRQ request, the server-side device receives a path of travel and builds a list to store interest points and a min-heap to store split points, iteratively retrieving split points from the min-heap, and reporting the CRQ result progressively until a termination condition is reached.

Voronoi diagram-based algorithm for efficient progressive continuous range query for moving objects

Systems and methods for performing a mobile range query are provided. A system can include a first computer readable medium configured to iteratively transmit a mobile range query, as well as a second computer readable medium configured to: receive a mobile range query; compute a range query result; build two min-heaps that contain in-border interest points and out-border intersect points respectively; construct an initial candidate safe region by popping top elements in the two min-heaps while they are not empty; computing the intersections of the domain region of the top elements and the candidate safe region and redefining the candidate safe region using the intersections; and return the mobile range query results to the first medium.

Voronoi-based efficient algorithm for range query monitoring for mobile devices and central database servers

Methods and systems for computing continuous k nearest neighbor (CkNN) queries in location based services for moving objects, to produce ordered kNN query results in a continuous and progressive manner, are provided. One method comprises receiving a continuous k nearest neighbor query, computing the initial set comprised of the k interest points nearest to the reference point and a set of remaining nodes stored in a distance-priority queue, generating and storing split points in a min-heap, iteratively moving current reference point to the nearest split point, swapping interest points, updating the corresponding split points in the min-heap, and reporting the kNN result progressively until a termination condition is reached.

Efficient progressive continuous k-nearest neighbor query algorithm for moving objects with a tree-like index

Systems and methods for performing a mobile window query are provided. A method can include transmitting a mobile window query, determining which interest point falls within a query window, defining a potential safe region, refining the safe region utilizing the surrounding interest points, and returning the interest points and safe region to a user.

Window query monitoring for mobile devices and central database servers with a tree-like index

Methods and apparatuses for providing a k-nearest neighbor for location based services are provided. A method can include querying a database to detect a plurality of interest points within a predetermined distance of the user device using a kNN algorithm, organizing the interest points within a Voronoi tree, and continuously return a position specific result of relevant interest points.

Voronoi diagram-based algorithm for efficient progressive continuous k-nearest neighbor query for moving objects

Methods for progressive continuous range query (PCRQ) are provided. A method can include using branch-and-bound to index interest points with a tree-index and generating a nearest enter split-point for a root node in the tree-index and adding to min-heap. Next, whether min-heap has more elements and whether a next split-point in min-heap is closer than a destination can be determined. Whether a query point has reached a split-point can be investigated followed by retrieving an entry that has generated the split-point. The split-point can be then be removed from min-heap.

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Miami, FL, United States of America

Mingjin Zhang