Results 1  10
of
10
HLDB: Locationbased services in databases
 In Proceedings of the 20th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems (GIS’12), 339–348. ACM Press. Best Paper Award
, 2012
"... This paper introduces HLDB, the first practical system that can answer exact spatial queries on continental road networks entirely within a database. HLDB is based on hub labels (HL), the fastest pointtopoint algorithm for road networks, and its queries are implemented (quite naturally) in stan ..."
Abstract

Cited by 7 (4 self)
 Add to MetaCart
(Show Context)
This paper introduces HLDB, the first practical system that can answer exact spatial queries on continental road networks entirely within a database. HLDB is based on hub labels (HL), the fastest pointtopoint algorithm for road networks, and its queries are implemented (quite naturally) in standard SQL. Within the database, HLDB answers exact distance queries and retrieves full shortestpath descriptions in real time, even on networks with tens of millions of vertices. The basic algorithm can be extended in a natural way (still in SQL) to answer much more sophisticated queries, such as finding the ten closest fastfood restaurants. We also introduce efficient new HLbased algorithms for even harder problems, such as best via point, ride sharing, and point of interest prediction. The HLDB framework makes it easy to implement these algorithms in SQL, enabling interactive applications on continental road networks.
TopK Nearest Keyword Search on Large Graphs
"... It is quite common for networks emerging nowadays to have labels or textual contents on the nodes. On such networks, we study the problem of topk nearest keyword (kNK) search. In a network G modeled as an undirected graph, each node is attached with zero or more keywords, and each edge is assigned ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
(Show Context)
It is quite common for networks emerging nowadays to have labels or textual contents on the nodes. On such networks, we study the problem of topk nearest keyword (kNK) search. In a network G modeled as an undirected graph, each node is attached with zero or more keywords, and each edge is assigned with a weight measuring its length. Given a query node q in G and a keyword λ, a kNK query seeks k nodes which contain λ and are nearest to q. kNK is not only useful as a standalone query but also as a building block for tackling complex graph pattern matching problems. The key to an accurate kNK result is a precise shortest distance estimation in a graph. Based on the latest distance oracle technique, we build a shortest path tree for a distance oracle and use the tree distance as a more accurate estimation. With such representation, the original kNK query on a graph can be reduced to answering the query on a set of trees and then assembling the results obtained from the trees. We propose two efficient algorithms to report the exact kNK result on a tree. One is query time optimized for a scenario when a small number of result nodes are of interest to users. The other handles kNK queries for an arbitrarily large k efficiently. In obtaining a kNK result on a graph from that on trees, a global storage technique is proposed to further reduce the index size and the query time. Extensive experimental results conform with our theoretical findings, and demonstrate the effectiveness and efficiency of our kNK algorithms on large real graphs. 1.
Roads Belong in Databases
"... The popularity of locationbased services and the need to perform realtime processing on them has led to an interest in queries on road networks, such as finding shortest paths and finding nearest neighbors. The challenge here is that the efficient execution of operations usually involves the compu ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
(Show Context)
The popularity of locationbased services and the need to perform realtime processing on them has led to an interest in queries on road networks, such as finding shortest paths and finding nearest neighbors. The challenge here is that the efficient execution of operations usually involves the computation of distance along a spatial network instead of “as the crow flies, ” which is not simple. This requires the precomputation of the shortest paths and network distance between every pair of points (i.e., vertices) with as little space as possible rather than having to store the n 2 shortest paths and distances between all pairs. This problem is related to a ‘holy grail ’ problem in databases of how to incorporate road networks into relational databases. A data structure called a road network oracle is introduced that resides in a database and enables the processing of many operations on road networks with just the aid of relational operators. Two implementations of road network oracles are presented. 1
Towards online shortest path computation
 IEEE Trans. Knowl. Data Eng
, 2014
"... Abstract—The online shortest path problem aims at computing the shortest path based on live traffic circumstances. This is very important in modern car navigation systems as it helps drivers to make sensible decisions. To our best knowledge, there is no efficient system/solution that can offer affor ..."
Abstract

Cited by 3 (1 self)
 Add to MetaCart
(Show Context)
Abstract—The online shortest path problem aims at computing the shortest path based on live traffic circumstances. This is very important in modern car navigation systems as it helps drivers to make sensible decisions. To our best knowledge, there is no efficient system/solution that can offer affordable costs at both client and server sides for online shortest path computation. Unfortunately, the conventional clientserver architecture scales poorly with the number of clients. A promising approach is to let the server collect live traffic information and then broadcast them over radio or wireless network. This approach has excellent scalability with the number of clients. Thus, we develop a new framework called live traffic index (LTI) which enables drivers to quickly and effectively collect the live traffic information on the broadcasting channel. An impressive result is that the driver can compute/update their shortest path result by receiving only a small fraction of the index. Our experimental study shows that LTI is robust to various parameters and it offers relatively short tunein cost (at client side), fast query response time (at client side), small broadcast size (at server side), and light maintenance time (at server side) for online shortest path problem. Index Terms—Spatial databases; Vehicle driving; Broadcasting F
MemoryEfficient Algorithms for Spatial Network Queries
"... Abstract — Incrementally finding thek nearest neighbors (kNN) in a spatial network is an important problem in locationbased services. One method (INE) simply applies Dijkstra’s algorithm. Another method (IER) computes the k nearest neighbors using Euclidean distance followed by computing their corr ..."
Abstract

Cited by 2 (0 self)
 Add to MetaCart
(Show Context)
Abstract — Incrementally finding thek nearest neighbors (kNN) in a spatial network is an important problem in locationbased services. One method (INE) simply applies Dijkstra’s algorithm. Another method (IER) computes the k nearest neighbors using Euclidean distance followed by computing their corresponding network distances, and then incrementally finds the next nearest neighbors in order of increasing Euclidean distance until finding one whose Euclidean distance is greater than the current k nearest neighbor in terms of network distance. The LBC method improves on INE by avoiding the visit of nodes that cannot possibly lead to the k nearest neighbors by using a Euclidean heuristic estimator, and on IER by avoiding the repeated visits to nodes in the spatial network that appear on the shortest paths to different members of the k nearest neighbors by performing multiple instances of heuristic search using a Euclidean heuristic
Outputsensitive wellseparated pair decompositions for dynamic point sets. Unpublished manuscript
 In Proc. 19th Annu. ACMSIAM Sympos. Discrete Algorithms
, 2013
"... ABSTRACT The wellseparated pair decomposition (WSPD) is a fundamental structure in computational geometry. Given a set P of n points in ddimensional space and a positive separation parameter s, an sWSPD is a concise representation of all the O(n 2 ) pairs of P requiring only O(s d n) storage. Th ..."
Abstract

Cited by 1 (1 self)
 Add to MetaCart
(Show Context)
ABSTRACT The wellseparated pair decomposition (WSPD) is a fundamental structure in computational geometry. Given a set P of n points in ddimensional space and a positive separation parameter s, an sWSPD is a concise representation of all the O(n 2 ) pairs of P requiring only O(s d n) storage. The WSPD has numerous applications in spatial data processing, such as computing spanner graphs, minimum spanning trees, shortestpath oracles, and statistics on interpoint distances. We consider the problem of maintaining a WSPD when points are inserted to or deleted from P . Worstcase arguments suggest that the addition or deletion of a single point could result in the generation (or removal) up to Ω(s d ) pairs, which can be unacceptably high in many applications. Fortunately, the actual number of well separated pairs can be significantly smaller in practice, particularly when the points are well clustered. This suggests the importance of being able to respond to insertions and deletions in a manner that is output sensitive, that is, whose running time depends on the actual number of pairs that have been added or removed. We present the first outputsensitive algorithms for maintaining a WSPD of a point set under insertion and deletion. We show that our algorithms are nearly optimal, in the sense that these operations can be performed in time that is roughly equal to the number of changes to the WSPD.
Foundations of Nearest Neighbor Queries in Euclidean Space *
"... Abstract A number of approaches to computing nearest neighbor queries in Euclidean space are presented. This includes the depthfirst and bestfirst methods as well as a comparison. The best first method is shown to be capable of being extended to report the neighboring objects in increasing order ..."
Abstract
 Add to MetaCart
Abstract A number of approaches to computing nearest neighbor queries in Euclidean space are presented. This includes the depthfirst and bestfirst methods as well as a comparison. The best first method is shown to be capable of being extended to report the neighboring objects in increasing order from the query object so that the search can be incremental and there is no need to know the value of k in advance. The incremental algorithm is shown to be modifiable to also work for objects that have spatial extent instead of being restricted to be point objects. The bestfirst method is also shown to yield the k approximate nearest neighbors give an error tolerance value. Keywords: nearest neighbor query, depthfirst nearest neighbor query, bestfirst nearest neighbor query, incremental nearest neighbor query, approximate nearest neighbor query
Realtime Response of Shortest Path Computation
"... Computing the shortest path between two locations in a network is an important and fundamental problem that finds applications in a wide range of fields. This problem has attracted considerable research interest and led to a plethora of algorithms. However, existing approaches have two main drawba ..."
Abstract
 Add to MetaCart
(Show Context)
Computing the shortest path between two locations in a network is an important and fundamental problem that finds applications in a wide range of fields. This problem has attracted considerable research interest and led to a plethora of algorithms. However, existing approaches have two main drawbacks: complete path computation before movement and reprocessing when node failure occurs. In this paper, two novel algorithms, RSP (Realtime Shortest Path) and RSP+ (Realtime Shortest Path Plus), are proposed to handle both shortcomings. We perform a network preprocessing to ensure a constant time response of retrieving the shortest route for an arbitrary node to an important set of destinations. RSP+ further divides the complete path into smaller partial paths, which can then be computed in parallel. Besides, considering the continuous changes of the network, like traffic jams and road constructions, where certain paths are blocked, a fast recovery method to efficiently find the best alternative route is integrated into RSP+. Empirical studies have shown that RSP+ can achieve an average query processing time of 0.8 microseconds. Besides, the effectiveness of the recovery mechanism demonstrates that alternative routes can be obtained to avoid unavailable areas.
DYNAMIC DATA STRUCTURES FOR GEOMETRIC SEARCH AND RETRIEVAL
, 2013
"... Data structures for geometric search and retrieval are of significant interest in areas such as computational geometry, computer graphics, and computer vision. The focus of this dissertation is on the design of efficient dynamic data structures for use in approximate retrieval problems in multidimen ..."
Abstract
 Add to MetaCart
Data structures for geometric search and retrieval are of significant interest in areas such as computational geometry, computer graphics, and computer vision. The focus of this dissertation is on the design of efficient dynamic data structures for use in approximate retrieval problems in multidimensional Euclidean space. A number of data structures have been proposed for storing multidimensional point sets. We will focus on quadtreebased structures. Quadtreebased structures possess a number of desirable properties, and they have been shown to be useful in solving a wide variety of query problems, especially when approximation is involved. First, we introduce two dynamic quadtreebased data structures for storing a set of points in space, called the quadtreap and the splay quadtree. The quadtreap is a randomized variant of a quadtree that supports insertion and deletion and has logarithmic height with high probability. The splay quadtree is also a quadtree variant, but this data structure is selfadjusting, that is, it rebalances itself depending on the access pattern. It supports efficient insertion and deletion in the amortized sense. We also study how to dynamically maintain an important geometric structure,