A link-based storage scheme for efficient aggregate query processing on clustered road networks

Demir, Engin; Aykanat, Cevdet; Cambazoğlu, B. Barla

doi:10.1016/j.is.2009.03.005

Cited by 9 publications

(6 citation statements)

References 43 publications

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“…In this model, records are clustered into disk pages by hypergraph partitioning, where the partitioning objective corresponds to minimizing the disk access cost of GS operations in network queries. In [16], we introduce the link-based storage scheme, where each link together with its connectivity information is stored in a data record. We also propose a clustering hypergraph model for this new storage scheme.…”

Section: Related Workmentioning

confidence: 99%

Efficient successor retrieval operations for aggregate query processing on clustered road networks

Demir

Aykanat

2010

Information Sciences

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Get-Successors (GS) which retrieves all successors of a junction is a kernel operation used to facilitate aggregate computations in road network queries. Efficient implementation of the GS operation is crucial since the disk access cost of this operation constitutes a considerable portion of the total query processing cost. Firstly, we propose a new successor retrieval operation Get-Unevaluated-Successors (GUS), which retrieves only the unevaluated successors of a given junction. The GUS operation is an efficient implementation of the GS operation, where the candidate successors to be retrieved are pruned according to the properties and state of the algorithm. Secondly, we propose a hypergraph-based model for clustering successively retrieved junctions by the GUS operations to the same pages. The proposed model utilizes query logs to correctly capture the disk access cost of GUS operations. The proposed GUS operation and associated clustering model are evaluated for two different instances of GUS operations which typically arise in Dijkstra's single source shortest path algorithm and incremental network expansion framework. Our simulation results show that the proposed successor retrieval operation together with the proposed clustering hypergraph model is quite effective in reducing the number of disk accesses in query processing. © 2010 Published by Elsevier Inc

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Section: Related Workmentioning

confidence: 99%

Efficient successor retrieval operations for aggregate query processing on clustered road networks

Demir

Aykanat

2010

Information Sciences

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“…First, for each query q, we count the number of data items that are in A, B and AB state among the data items requested by q (lines 1-5). Here, State is a vector which holds the states of the data items, i.e., State(d) stores the current state of data item d. Then, we calculate the move gain g m (d) and the replication gain g r (d) of each data item (6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17). Note that only non-replicated data items are amenable to move and replication.…”

Section: Proposed Approachmentioning

confidence: 99%

“…The vertex weights represent the data item sizes and net weights represent the query frequencies. Recently, hypergraph models have also been applied for clustering purposes in data mining ( [5]) and road network systems ( [6], [7]). …”

Section: Introductionmentioning

confidence: 99%

Selective Replicated Declustering for Arbitrary Queries

Oktay

Türk

Aykanat

2009

Lecture Notes in Computer Science

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Abstract. Data declustering is used to minimize query response times in data intensive applications. In this technique, query retrieval process is parallelized by distributing the data among several disks and it is useful in applications such as geographic information systems that access huge amounts of data. Declustering with replication is an extension of declustering with possible data replicas in the system. Many replicated declustering schemes have been proposed. Most of these schemes generate two or more copies of all data items. However, some applications have very large data sizes and even having two copies of all data items may not be feasible. In such systems selective replication is a necessity. Furthermore, existing replication schemes are not designed to utilize query distribution information if such information is available. In this study we propose a replicated declustering scheme that decides both on the data items to be replicated and the assignment of all data items to disks when there is limited replication capacity. We make use of available query information in order to decide replication and partitioning of the data and try to optimize aggregate parallel response time. We propose and implement a Fiduccia-Mattheyses-like iterative improvement algorithm to obtain a two-way replicated declustering and use this algorithm in a recursive framework to generate a multi-way replicated declustering. Experiments conducted with arbitrary queries on real datasets show that, especially for low replication constraints, the proposed scheme yields better performance results compared to existing replicated declustering schemes.

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“…Cao Zhengcai [6] put forward the road for the basic elements, the relationship between road traffic information and road network, from network information and traffic information representation method and path search efficiency aspects, set up to meet the demand of actual road network model; literature [7] methods to construct the network topology model based on trajectory, by detection of topological relation model of road network extraction of key points, based on the space partition set and network topology model of the original trajectory data mining sequence data conversion and frequent pattern. Demir and other [8] construct a clustering hyper-graph model, and reduce the storage capacity of road network data by transforming the node based data storage mode into the data storage method based on the road section.…”

Section: Introductionmentioning

confidence: 99%

Research on Pedestrian Route Planning Algorithm Based on Low Exhaust Intake

Xu¹,

Chen²,

Ruan³

2018

dtcse

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The main pollution source of urban air quality is vehicle exhaust pollution, in which a variety of toxic and harmful substances seriously affect the health. In this paper, a pedestrian path planning algorithm based on low exhaust gas intake is proposed. The vehicle exhaust collection device is used to collect and analyze the concentration of harmful gases on the road edge, and calculate the air quality index of each section by AQI calculation method. In order to reduce the intake of harmful gas in the existing road network model, the route planning of the minimum harmful gas intake from the starting point to the destination node is given by using the A* search algorithm. Experiments show that the algorithm can effectively avoid the large traffic flow and serious air pollution section.

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A link-based storage scheme for efficient aggregate query processing on clustered road networks

Cited by 9 publications

References 43 publications

Efficient successor retrieval operations for aggregate query processing on clustered road networks

Efficient successor retrieval operations for aggregate query processing on clustered road networks

Selective Replicated Declustering for Arbitrary Queries

Research on Pedestrian Route Planning Algorithm Based on Low Exhaust Intake

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