Results 1  10
of
48
Hierarchical encoded path views for path query processing: An optimal model and its performance evaluation
 IEEE Transactions on Knowledge and Data Engineering
, 1998
"... Abstract—Efficient path computation is essential for applications such as intelligent transportation systems (ITS) and network routing. In ITS navigation systems, many path requests can be submitted over the same, typically huge, transportation network within a small time window. While path precompu ..."
Abstract

Cited by 87 (2 self)
 Add to MetaCart
(Show Context)
Abstract—Efficient path computation is essential for applications such as intelligent transportation systems (ITS) and network routing. In ITS navigation systems, many path requests can be submitted over the same, typically huge, transportation network within a small time window. While path precomputation (path view) would provide an efficient path query response, it raises three problems which must be addressed: 1) precomputed paths exceed the current computer main memory capacity for large networks; 2) diskbased solutions are too inefficient to meet the stringent requirements of these target applications; and 3) path views become too costly to update for large graphs (resulting in outofdate query results). We propose a hierarchical encoded path view (HEPV) model that addresses all three problems. By hierarchically encoding partial paths, HEPV reduces the view encoding time, updating time and storage requirements beyond previously known path precomputation techniques, while significantly minimizing path retrieval time. We prove that paths retrieved over HEPV are optimal. We present complete solutions for all phases of the HEPV approach, including graph partitioning, hierarchy generation, path view encoding and updating, and path retrieval. In this paper, we also present an indepth experimental evaluation of HEPV based on both synthetic and real GIS networks. Our results confirm that HEPV offers advantages over alternative path finding approaches in terms of performance and space efficiency. Index Terms—Path queries, path view materialization, hierarchical path search, GIS databases, graph partitioning. 1
Dijkstra's Algorithm OnLine: An Empirical Case Study from Public Railroad Transport
 JOURNAL OF EXPERIMENTAL ALGORITHMICS
, 2000
"... ..."
(Show Context)
CCAM: ConnectivityClustered Access Method for Networks and Network Computations
, 1993
"... ..."
(Show Context)
Geometric SpeedUp Techniques for Finding Shortest Paths in Large Sparse Graphs
, 2003
"... In this paper, we consider Dijkstra's algorithm for the single source single target shortest paths problem in large sparse graphs. The goal is to reduce the response time for online queries by using precomputed information. For the result of the preprocessing, we admit at most linear space. ..."
Abstract

Cited by 59 (15 self)
 Add to MetaCart
(Show Context)
In this paper, we consider Dijkstra's algorithm for the single source single target shortest paths problem in large sparse graphs. The goal is to reduce the response time for online queries by using precomputed information. For the result of the preprocessing, we admit at most linear space. We assume that a layout of the graph is given. From this layout, in the preprocessing, we determine for each edge a geometric object containing all nodes that can be reached on a shortest path starting with that edge. Based on these geometric objects, the search space for online computation can be reduced significantly. We present an extensive experimental study comparing the impact of different types of objects. The test data we use are traffic networks, the typical field of application for this scenario.
Introduction to Mobile Computing
 In Mobile Computing
, 1996
"... A CJ.P » Catalogue record for this book is available from the Library of Congress. Copyright ® 1996 by Kluwer Academic Publishers All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, mechanical, photocopying, re ..."
Abstract

Cited by 49 (0 self)
 Add to MetaCart
A CJ.P » Catalogue record for this book is available from the Library of Congress. Copyright ® 1996 by Kluwer Academic Publishers All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, mechanical, photocopying, recording, or otherwise, without the prior written permission of
Finding fastest paths on a road network with speed patterns
 In Proc. Int. Conf. on Data Engineering (ICDE’06
, 2006
"... This paper proposes and solves the TimeInterval All Fastest Path (allFP) query. Given a userdefined leaving or arrival time interval I, a source node s and an end node e, allFP asks for a set of all fastest paths from s to e, one for each subinterval of I. Note that the query algorithm should fin ..."
Abstract

Cited by 45 (0 self)
 Add to MetaCart
(Show Context)
This paper proposes and solves the TimeInterval All Fastest Path (allFP) query. Given a userdefined leaving or arrival time interval I, a source node s and an end node e, allFP asks for a set of all fastest paths from s to e, one for each subinterval of I. Note that the query algorithm should find a partitioning of I into subintervals. Existing methods can only be used to solve a very special case of the problem, when the leaving time is a single time instant. A straightforward solution to the allFP query is to run existing methods many times, once for every time instant in I. This paper proposes a solution based on novel extensions to the A * algorithm. Instead of expanding the network many times, we expand once. The travel time on a path is kept as a function of leaving time. Methods to combine traveltime functions are provided to expand a path. A novel lowerbound estimator for travel time is proposed. Performance results reveal that our method is more efficient and more accurate than the discretetime approach. 1
Aggregate nearest neighbor queries in road networks
 TKDE
, 2005
"... Abstract—Aggregate nearest neighbor queries return the object that minimizes an aggregate distance function with respect to a set of query points. Consider, for example, several users at specific locations (query points) that want to find the restaurant (data point), which leads to the minimum sum o ..."
Abstract

Cited by 44 (0 self)
 Add to MetaCart
(Show Context)
Abstract—Aggregate nearest neighbor queries return the object that minimizes an aggregate distance function with respect to a set of query points. Consider, for example, several users at specific locations (query points) that want to find the restaurant (data point), which leads to the minimum sum of distances that they have to travel in order to meet. We study the processing of such queries for the case where the position and accessibility of spatial objects are constrained by spatial (e.g., road) networks. We consider alternative aggregate functions and techniques that utilize Euclidean distance bounds, spatial access methods, and/or network distance materialization structures. Our algorithms are experimentally evaluated with synthetic and real data. The results show that their relative performance depends on the problem characteristics. Index Terms—Query processing, spatial databases, spatial databases and GIS, locationdependent and sensitive. 1
The optimallocation query
 In SSTD
, 2005
"... Abstract. We propose and solve the optimallocation query in spatial databases. Given a set S of sites, a set O of weighted objects, and a spatial region Q, the optimallocation query returns a location in Q with maximum influence. Here the influence of a location l is the total weight of its RNNs, ..."
Abstract

Cited by 40 (2 self)
 Add to MetaCart
(Show Context)
Abstract. We propose and solve the optimallocation query in spatial databases. Given a set S of sites, a set O of weighted objects, and a spatial region Q, the optimallocation query returns a location in Q with maximum influence. Here the influence of a location l is the total weight of its RNNs, i.e. the total weight of objects in O that are closer to l than to any site in S. This new query has practical applications, but is very challenging to solve. Existing work on computing RNNs assumes a single query location, and thus cannot be used to compute optimal locations. The reason is that there are infinite candidate locations in Q. If we check a finite set of candidate locations, the result can be inaccurate, i.e. the revealed location may not have maximum influence. This paper proposes three methods that accurately compute optimal locations. The first method uses a standard R*tree. To compute an optimal location, the method retrieves certain objects from the R*tree and sends them as a stream to a planesweep algorithm, which uses a new data structure called the aSBtree to ensure query efficiency. The second method is based on a new index structure called the OLtree, which novelly extends the kdBtree to store segmented rectangular records. The OLtree is only of theoretical usage for it is not space efficient. The most practical approach is based on a new index structure called the Virtual OLtree. These methods are theoretically and experimentally evaluated. 1
Finding timedependent shortest paths over large graphs
 In Proc. EDBT
, 2008
"... The spatial and temporal databases have been studied widely and intensively over years. In this paper, we study how to answer queries of finding the best departure time that minimizes the total travel time from a place to another, over a road network, where the traffic conditions dynamically change ..."
Abstract

Cited by 35 (1 self)
 Add to MetaCart
(Show Context)
The spatial and temporal databases have been studied widely and intensively over years. In this paper, we study how to answer queries of finding the best departure time that minimizes the total travel time from a place to another, over a road network, where the traffic conditions dynamically change from time to time. We study a generalized form of this problem, called the timedependent shortestpath problem. A timedependent graph GT is a graph that has an edgedelay function, wi,j(t), associated with each edge (vi, vj), to be stored in a database. The edgedelay function wi,j(t) specifies how much time it takes to travel from node vi to node vj, if it departs from vi at time t. A userspecified query is to ask the minimumtraveltime path, from a source node, vs, to a destination node, ve, over the timedependent graph, GT, with the best departure time to be selected from a time interval T. We denote this user query as LTT(vs, ve, T) over GT. The challenge of this problem is the added complexity due to the time dependency in the timedependent graph. That is, edge delays are not constants, and can vary from time to time. In this paper, we propose a novel algorithm to find the minimumtraveltime path with the best departure time for a LTT(vs, ve, T) query over a large graph GT. Our approach outperforms existing algorithms in terms of both time complexity in theory and efficiency in practice. We will discuss the design of our algorithm, together with its correctness and complexity. We conducted extensive experimental studies over large graphs and will report our findings. 1.
Using Multilevel Graphs for Timetable Information in Railway Systems
 IN PROCEEDINGS 4TH WORKSHOP ON ALGORITHM ENGINEERING AND EXPERIMENTS (ALENEX 2002), VOLUME 2409 OF SPRINGER LNCS
, 2002
"... In many fields of application shortest path finding problems in very large graphs arise. Scenarios where large numbers ofonW##O queries for shortest paths have to be processedin realtime appear for examplein tra#cinc5###HF5 systems.In such systems, the techn5Ww# con sidered to speed up the shortes ..."
Abstract

Cited by 32 (14 self)
 Add to MetaCart
In many fields of application shortest path finding problems in very large graphs arise. Scenarios where large numbers ofonW##O queries for shortest paths have to be processedin realtime appear for examplein tra#cinc5###HF5 systems.In such systems, the techn5Ww# con sidered to speed up the shortest pathcomputation are usually basedon precomputed incomputed5 On approach proposedoften in thiscon text is a spacereduction where precomputed shortest paths are replaced by sin## edges with weight equal to thelenOq of the corresponres shortest path.In this paper, we give a first systematic experimen tal study of such a spacereduction approach. Wein troduce theconOkW of multilevel graph decomposition Foron specificapplication scenica from the field of timetable information in public tranc ort, we perform a detailed anai ysisan experimen tal evaluation of shortest path computation based on multilevel graph decomposition.