Results 1  10
of
25
Adding Regular Expressions to Graph Reachability and Pattern Queries
 Frontiers of Computer Science
, 2012
"... Abstract—It is increasingly common to find graphs in which edges bear different types, indicating a variety of relationships. For such graphs we propose a class of reachability queries and a class of graph patterns, in which an edge is specified with a regular expression of a certain form, expressin ..."
Abstract

Cited by 30 (6 self)
 Add to MetaCart
(Show Context)
Abstract—It is increasingly common to find graphs in which edges bear different types, indicating a variety of relationships. For such graphs we propose a class of reachability queries and a class of graph patterns, in which an edge is specified with a regular expression of a certain form, expressing the connectivity in a data graph via edges of various types. In addition, we define graph pattern matching based on a revised notion of graph simulation. On graphs in emerging applications such as social networks, we show that these queries are capable of finding more sensible information than their traditional counterparts. Better still, their increased expressive power does not come with extra complexity. Indeed, (1) we investigate their containment and minimization problems, and show that these fundamental problems are in quadratic time for reachability queries and are in cubic time for pattern queries. (2) We develop an algorithm for answering reachability queries, in quadratic time as for their traditional counterpart. (3) We provide two cubictime algorithms for evaluating graph pattern queries based on extended graph simulation, as opposed to the NPcompleteness of graph pattern matching via subgraph isomorphism. (4) The effectiveness, efficiency and scalability of these algorithms are experimentally verified using reallife data and synthetic data. I.
Path Oracles for Spatial Networks
, 2009
"... The advent of locationbased services has led to an increased demand for performing operations on spatial networks in real time. The challenge lies in being able to cast operations on spatial networks in terms of relational operators so that they can be performed in the context of a database. A line ..."
Abstract

Cited by 26 (8 self)
 Add to MetaCart
(Show Context)
The advent of locationbased services has led to an increased demand for performing operations on spatial networks in real time. The challenge lies in being able to cast operations on spatial networks in terms of relational operators so that they can be performed in the context of a database. A linearsized construct termed a path oracle is introduced that compactly encodes the n2 shortest paths between every pair of vertices in a spatial network having n vertices thereby reducing each of the paths to a single tuple in a relational database and enables finding shortest paths by repeated application of a single SQL SELECT operator. The construction of the path oracle is based on the observed coherence between the spatial positions of both source and destination vertices and the shortest paths between them which facilitates the aggregation of source and destination vertices into groups that share common vertices or edges on the shortest paths between them. With the aid of the WellSeparated Pair (WSP) technique, which has been applied to spatial networks using the network distance measure, a path oracle is proposed that takes O(sdn) space, where s is empirically estimated to be around 12 for road networks, but that can retrieve an intermediate link in a shortest path in O(logn) time using a Btree. An additional construct termed the pathdistance oracle of size O(n · max(sd, 1 d ε)) (empirically (n · max(122, 2.5 2 ε))) is proposed that can retrieve an intermediate vertex as well as an εapproximation of the network distances in O(logn) time using a Btree. Experimental results indicate that the proposed oracles are linear in n which means that they are scalable and can enable complicated query processing scenarios on massive spatial network datasets.
Continuous Reverse k Nearest Neighbors Queries in . . .
 THE VLDB JOURNAL
"... In this paper, we study the problem of continuous monitoring of reverse ..."
Abstract

Cited by 7 (2 self)
 Add to MetaCart
In this paper, we study the problem of continuous monitoring of reverse
Continuous Detour Queries in Spatial Networks
"... We study the problem of finding the shortest route between two locations that includes a stopover of a given type. An example scenario of this problem is given as follows: “On the way to Bob’s place, Alice searches for a nearby takeaway Italian restaurant to buy a pizza. ” Assuming that Alice is i ..."
Abstract

Cited by 3 (2 self)
 Add to MetaCart
We study the problem of finding the shortest route between two locations that includes a stopover of a given type. An example scenario of this problem is given as follows: “On the way to Bob’s place, Alice searches for a nearby takeaway Italian restaurant to buy a pizza. ” Assuming that Alice is interested in minimizing the total trip distance, this scenario can be modelled as a query where the current Alice’s location (start) and Bob’s place (destination) function as query points. Based on these two query points, we find the minimum detour object (MDO), i.e., a stopover that minimizes the sum of the distances: (i) from the start to the stopover, and (ii) from the stopover to the destination. In a realistic locationbased application environment, a user can be indecisive about committing to a particular detour option. The user may wish to browse multiple (k) MDOs before making a decision. Furthermore, when a user moves, the kMDO results at one location may become obsolete. We propose a method for continuous detour query (CDQ) processing based on incremental construction of a shortest path tree. We conducted experimental studies to compare the performance of our proposed method against two methods derived from existing knearest neighbor querying techniques using real roadnetwork datasets. Experimental results show that our proposed method significantly outperforms the two competitive techniques.
MOIR/MT: Monitoring LargeScale Road Network Traffic in RealTime
"... Floating Car Data (FCD) provides an economic complement to infrastructurebased traffic monitoring systems. Based on our previous MOIR platform [5], we use FCD as the data source for largescale realtime traffic monitoring. This new function brings a challenge of efficiently handling of streaming d ..."
Abstract

Cited by 3 (2 self)
 Add to MetaCart
(Show Context)
Floating Car Data (FCD) provides an economic complement to infrastructurebased traffic monitoring systems. Based on our previous MOIR platform [5], we use FCD as the data source for largescale realtime traffic monitoring. This new function brings a challenge of efficiently handling of streaming data from a very large number of moving objects. Server overload problems can occur when a system fails to process data and queries in realtme, which can lead to critical issues such as unbounded delay accumulation, lost monitoring accuracy or lack of spontaneity. These problems can be addressed by adopting suitable load dropping decisions. In this work, we demonstrate several load shedding techniques, focusing on decisionmaking based on data attributes. With the end results being quantified and visualized using real data for a large city, this proofofconcept system provides a convincing way of validating our ideas. 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
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
Large Scale Realtime Ridesharing with Service Guarantee on Road Networks ∗
"... Urban traffic gridlock is a familiar scene. At the same time, the mean occupancy rate of personal vehicle trips in the United States is only 1.6 persons per vehicle mile. Ridesharing has the potential to solve many environmental, congestion, pollution, and energy problems. In this paper, we introdu ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
(Show Context)
Urban traffic gridlock is a familiar scene. At the same time, the mean occupancy rate of personal vehicle trips in the United States is only 1.6 persons per vehicle mile. Ridesharing has the potential to solve many environmental, congestion, pollution, and energy problems. In this paper, we introduce the problem of large scale realtime ridesharing with service guarantee on road networks. Trip requests are dynamically matched to vehicles while trip waiting and service time constraints are satisfied. We first propose two scheduling algorithms: a branchandbound algorithm and an integer programing algorithm. However, these algorithms do not adapt well to the dynamic nature of the ridesharing problem. Thus, we propose kinetic tree algorithms which are better suited to efficient scheduling of dynamic requests and adjust routes onthefly. We perform experiments on a large Shanghai taxi dataset. Results show that the kinetic tree algorithms outperform other algorithms significantly. 1.
Finding the Most Accessible Locations: Reverse Path Nearest Neighbor Query in Road Networks
 In SIGSPATIAL GIS
, 2011
"... In this paper, we propose and investigate a novel spatial query called Reverse Path Nearest Neighbor (RPNN) search to find the most accessible locations in road networks. Given a trajectory dataset and a list of location candidates specified by users, if a location o is the Path Nearest Neighbor ..."
Abstract

Cited by 3 (0 self)
 Add to MetaCart
(Show Context)
In this paper, we propose and investigate a novel spatial query called Reverse Path Nearest Neighbor (RPNN) search to find the most accessible locations in road networks. Given a trajectory dataset and a list of location candidates specified by users, if a location o is the Path Nearest Neighbor (PNN) of k trajectories, the influencefactor of o is defined as k and the RPNN query returns the location with the highest influencefactor. The RPNN query is an extension of the conventional Reverse Nearest Neighbor (RNN) search. It can be found in many important applications such as urban planning, facility allocation, traffic monitoring, etc. To answer the RPNN query efficiently, an effective trajectory data preprocessing technique is conducted in the first place. We cluster the trajectories into several groups according to their distribution. Based on the grouped trajectory data, a twophase solution is applied. First, we specify a tight search range over the trajectory and location datasets. The efficiency study reveals that our approach defines the minimum search area. Second, a series of optimization techniques are adopted to search the exact PNN for trajectories in the candidate set. By combining the PNN query results, we can retrieve the most accessible locations. The complexity analysis shows that our solution is optimal in terms of time cost. The performance of the proposed RPNN query processing is verified by extensive experiments based on real and synthetic trajectory data in road networks.
Continuous Monitoring of Distance Based Range Queries
 TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
"... Given a positive value r, a distance based range query returns the objects that lie within the distance r of the query location. In this paper, we focus on the distance based range queries that continuously change their locations in a Euclidean space. We present an efficient and effective monitoring ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
Given a positive value r, a distance based range query returns the objects that lie within the distance r of the query location. In this paper, we focus on the distance based range queries that continuously change their locations in a Euclidean space. We present an efficient and effective monitoring technique based on the concept of a safe zone. The safe zone of a query is the area with a property that while the query remains inside it, the results of the query remain unchanged. Hence, the query does not need to be reevaluated unless it leaves the safe zone. Our contributions are as follows. 1) We propose a technique based on powerful pruning rules and a unique access order which efficiently computes the safe zone and minimizes the I/O cost. 2) We theoretically determine and experimentally verify the expected distance a query moves before leaving the safe zone and, for majority of queries, the expected number of guard objects. 3) Our experiments demonstrate that the proposed approach is close to optimal and is an order of magnitude faster than a naïve algorithm. 4) We also extend our technique to monitor the queries in a road network. Our algorithm is up to two order of magnitude faster than a naïve algorithm.