1,171 research outputs found
CONTINUOUS MULTIQUERIES K-DOMINANT SKYLINE ON ROAD NETWORK
The increasing use of mobile devices makes spatial data worthy of consideration. To get maximum results, users often look for the best from a collection of objects. Among the algorithms that can be used is the skyline query. The algorithm looks for all objects that are not dominated by other objects in all of its attributes. However, data that has many attributes makes the query output a lot of objects so it is less useful for the user. k-dominant skyline queries can be a solution to reduce the output. Among the challenges is the use of skyline queries with spatial data and the many user preferences in finding the best object. This study proposes IKSR: the k-dominant skyline query algorithm that works in a road network environment and can process many queries that have the same subspace in one processing. This algorithm combines queries that operate on the same subspace and set of objects with different k values by computing from the smallest to the largest k. Optimization occurs when some data for larger k are precomputed when calculating the result for the smallest k so the Voronoi cell computing is not repeated. Testing is done by comparing with the naïve algorithm without precomputation. IKSR algorithm can speed up computing time two to three times compared to naïve algorithm
Collectively Simplifying Trajectories in a Database: A Query Accuracy Driven Approach
Increasing and massive volumes of trajectory data are being accumulated that
may serve a variety of applications, such as mining popular routes or
identifying ridesharing candidates. As storing and querying massive trajectory
data is costly, trajectory simplification techniques have been introduced that
intuitively aim to reduce the sizes of trajectories, thus reducing storage and
speeding up querying, while preserving as much information as possible.
Existing techniques rely mainly on hand-crafted error measures when deciding
which point to drop when simplifying a trajectory. While the hope may be that
such simplification affects the subsequent usability of the data only
minimally, the usability of the simplified data remains largely unexplored.
Instead of using error measures that indirectly may to some extent yield
simplified trajectories with high usability, we adopt a direct approach to
simplification and present the first study of query accuracy driven trajectory
simplification, where the direct objective is to achieve a simplified
trajectory database that preserves the query accuracy of the original database
as much as possible. Specifically, we propose a multi-agent reinforcement
learning based solution with two agents working cooperatively to collectively
simplify trajectories in a database while optimizing query usability. Extensive
experiments on four real-world trajectory datasets show that the solution is
capable of consistently outperforming baseline solutions over various query
types and dynamics.Comment: This paper has been accepted by ICDE 202
Continuous Spatial Query Processing:A Survey of Safe Region Based Techniques
In the past decade, positioning system-enabled devices such as smartphones have become most prevalent. This functionality brings the increasing popularity of
location-based services
in business as well as daily applications such as navigation, targeted advertising, and location-based social networking.
Continuous spatial queries
serve as a building block for location-based services. As an example, an Uber driver may want to be kept aware of the nearest customers or service stations. Continuous spatial queries require updates to the query result as the query or data objects are moving. This poses challenges to the query efficiency, which is crucial to the user experience of a service. A large number of approaches address this efficiency issue using the concept of
safe region
. A safe region is a region within which arbitrary movement of an object leaves the query result unchanged. Such a region helps reduce the frequency of query result update and hence improves query efficiency. As a result, safe region-based approaches have been popular for processing various types of continuous spatial queries. Safe regions have interesting theoretical properties and are worth in-depth analysis. We provide a comparative study of safe region-based approaches. We describe how safe regions are computed for different types of continuous spatial queries, showing how they improve query efficiency. We compare the different safe region-based approaches and discuss possible further improvements
- …