Voronoi-Based Safe Region Algorithm for Mobile Range Queries
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Solution Overview
Problem
Mobile Range Queries (MRQs) incur high network usage and processing costs due to the need for continuous reposting of queries as the client's position changes, as the results may be invalidated when moving outside a specified geographic range.
Innovation Solution
The use of Voronoi diagrams and Voronoi R-Trees to identify a safe region where the query result remains unchanged, allowing for the computation of range query results and storage in In-Border-Heap and Out-Border-Heap data structures, using modified R-tree range queries or Voronoi dynamic k-nearest neighbor algorithms to efficiently process MRQs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the client continuously reposts queries to the server when position changes, then the query result accuracy is maintained, but the network usage and processing costs increase significantly
Solution Approach 1:
The system pre-computes and returns a safe region along with the query results. This safe region is calculated in advance based on the current query parameters and points of interest, allowing the client to determine whether reposting is necessary before actually posting a new query. This preliminary action prevents unnecessary network traffic and server processing while ensuring query accuracy is maintained when needed.
Solution Approach 2:
The server provides feedback to the client in the form of a safe region boundary. The client uses this feedback to monitor its own position and determine when it has exited the safe region, triggering a new query only when necessary. This feedback mechanism creates an efficient closed-loop system that balances query accuracy with resource conservation.
2Loss of time
If the client reposts queries frequently to ensure up-to-date results, then the query result freshness is improved, but the computational overhead on the server increases
Solution Approach 1:
The server performs preliminary computation to determine the safe region where the query results remain valid. By calculating this region in advance and providing it to the client, the system enables the client to autonomously determine when reposting is necessary, significantly reducing the number of queries that reach the server and freeing up processing capacity.
Solution Approach 2:
The client uses the provided safe region information to self-monitor its position and autonomously decide when to repost queries. This self-service approach transfers the responsibility of query timing from the server to the client, reducing server computational overhead while maintaining result freshness through client-initiated reposts only when exiting the safe region.
3Loss of energy
If the safe region is calculated precisely to minimize reposting, then the network usage is reduced, but the initial computation complexity increases
Solution Approach 1:
The patent introduces Voronoi diagrams as an intermediary computational structure to efficiently calculate safe regions. By partitioning the space into Voronoi polygons based on points of interest, the system can determine safe regions through geometric operations on these polygons rather than exhaustive distance calculations, reducing computational complexity while maintaining precision.
Solution Approach 2:
The space is segmented into Voronoi polygons, each associated with a specific point of interest. This segmentation allows the safe region to be calculated as the intersection of relevant Voronoi polygons rather than considering all points of interest simultaneously, dividing the complex computation into manageable segments that can be processed efficiently.
Data Source
AI summary
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.