DMGA: A Distributed Shortest Path Algorithm for Multistage Graph

The multistage graph problem is a special kind of single-source single-sink shortest path problem. It is difficult even impossible to solve the large-scale multistage graphs using a single machine with sequential algorithms. There are many distributed graph computing systems that can solve this prob...

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Main Authors: Huanqing Cui, Ruixue Liu, Shaohua Xu, Chuanai Zhou
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Scientific Programming
Online Access:http://dx.doi.org/10.1155/2021/6639008
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spelling doaj-b5260e90cde349d9bdb2a8557f5679b32021-07-02T20:55:03ZengHindawi LimitedScientific Programming1875-919X2021-01-01202110.1155/2021/6639008DMGA: A Distributed Shortest Path Algorithm for Multistage GraphHuanqing Cui0Ruixue Liu1Shaohua Xu2Chuanai Zhou3College of Computer Science and EngineeringCollege of Computer Science and EngineeringCollege of Computer Science and EngineeringCollege of BusinessThe multistage graph problem is a special kind of single-source single-sink shortest path problem. It is difficult even impossible to solve the large-scale multistage graphs using a single machine with sequential algorithms. There are many distributed graph computing systems that can solve this problem, but they are often designed for general large-scale graphs, which do not consider the special characteristics of multistage graphs. This paper proposes DMGA (Distributed Multistage Graph Algorithm) to solve the shortest path problem according to the structural characteristics of multistage graphs. The algorithm first allocates the graph to a set of computing nodes to store the vertices of the same stage to the same computing node. Next, DMGA calculates the shortest paths between any pair of starting and ending vertices within a partition by the classical dynamic programming algorithm. Finally, the global shortest path is calculated by subresults exchanging between computing nodes in an iterative method. Our experiments show that the proposed algorithm can effectively reduce the time to solve the shortest path of multistage graphs.http://dx.doi.org/10.1155/2021/6639008
collection DOAJ
language English
format Article
sources DOAJ
author Huanqing Cui
Ruixue Liu
Shaohua Xu
Chuanai Zhou
spellingShingle Huanqing Cui
Ruixue Liu
Shaohua Xu
Chuanai Zhou
DMGA: A Distributed Shortest Path Algorithm for Multistage Graph
Scientific Programming
author_facet Huanqing Cui
Ruixue Liu
Shaohua Xu
Chuanai Zhou
author_sort Huanqing Cui
title DMGA: A Distributed Shortest Path Algorithm for Multistage Graph
title_short DMGA: A Distributed Shortest Path Algorithm for Multistage Graph
title_full DMGA: A Distributed Shortest Path Algorithm for Multistage Graph
title_fullStr DMGA: A Distributed Shortest Path Algorithm for Multistage Graph
title_full_unstemmed DMGA: A Distributed Shortest Path Algorithm for Multistage Graph
title_sort dmga: a distributed shortest path algorithm for multistage graph
publisher Hindawi Limited
series Scientific Programming
issn 1875-919X
publishDate 2021-01-01
description The multistage graph problem is a special kind of single-source single-sink shortest path problem. It is difficult even impossible to solve the large-scale multistage graphs using a single machine with sequential algorithms. There are many distributed graph computing systems that can solve this problem, but they are often designed for general large-scale graphs, which do not consider the special characteristics of multistage graphs. This paper proposes DMGA (Distributed Multistage Graph Algorithm) to solve the shortest path problem according to the structural characteristics of multistage graphs. The algorithm first allocates the graph to a set of computing nodes to store the vertices of the same stage to the same computing node. Next, DMGA calculates the shortest paths between any pair of starting and ending vertices within a partition by the classical dynamic programming algorithm. Finally, the global shortest path is calculated by subresults exchanging between computing nodes in an iterative method. Our experiments show that the proposed algorithm can effectively reduce the time to solve the shortest path of multistage graphs.
url http://dx.doi.org/10.1155/2021/6639008
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AT ruixueliu dmgaadistributedshortestpathalgorithmformultistagegraph
AT shaohuaxu dmgaadistributedshortestpathalgorithmformultistagegraph
AT chuanaizhou dmgaadistributedshortestpathalgorithmformultistagegraph
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