### Abstract

In a constrained shortest path (CSP) query, each edge in the road network is associated with both a length and a cost. Given an origin s, a destination t, and a cost constraint 9, the goal is to find the shortest path from s to t whose total cost does not exceed 9. Because exact CSP is NP-hard, previous work mostly focuses on approximate solutions. Even so, existing methods are still prohibitively expensive for large road networks. Two main reasons are (i) that they fail to utilize the special properties of road networks and (ii) that most of them process queries without indices; the few existing indices consume large amounts of memory and yet have limited effectiveness in reducing query costs. Motivated by this, we propose COLA, the first practical solution for approximate CSP processing on large road networks. COLA exploits the facts that a road network can be effectively partitioned, and that there exists a relatively small set of landmark vertices that commonly appear in CSP results. Accordingly, COLA indexes the vertices lying on partition boundaries, and applies an on-the-fly algorithm called A-Dijk for path computation within a partition, which effectively prunes paths based on landmarks. Extensive experiments demonstrate that on continent-sized road networks, COLA answers an approximate CSP query in sub-second time, whereas existing methods take hours. Interestingly, even without an index, the A-Dijk algorithm in COLA still outperforms previous solutions by more than an order of magnitude.

Original language | English |
---|---|

Pages (from-to) | 61-72 |

Number of pages | 12 |

Journal | Proceedings of the VLDB Endowment |

Volume | 10 |

Issue number | 2 |

DOIs | |

Publication status | Published - 1 Jan 2016 |

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### ASJC Scopus subject areas

- Computer Science (miscellaneous)
- Computer Science(all)

### Cite this

*Proceedings of the VLDB Endowment*,

*10*(2), 61-72. https://doi.org/10.14778/3015274.3015277

**Effective indexing for approximate constrained shortest path queries on large road networks.** / Wang, Sibo; Xiao, Xiaokui; Yang, Yin; Lin, Wenqing.

Research output: Contribution to journal › Conference article

*Proceedings of the VLDB Endowment*, vol. 10, no. 2, pp. 61-72. https://doi.org/10.14778/3015274.3015277

}

TY - JOUR

T1 - Effective indexing for approximate constrained shortest path queries on large road networks

AU - Wang, Sibo

AU - Xiao, Xiaokui

AU - Yang, Yin

AU - Lin, Wenqing

PY - 2016/1/1

Y1 - 2016/1/1

N2 - In a constrained shortest path (CSP) query, each edge in the road network is associated with both a length and a cost. Given an origin s, a destination t, and a cost constraint 9, the goal is to find the shortest path from s to t whose total cost does not exceed 9. Because exact CSP is NP-hard, previous work mostly focuses on approximate solutions. Even so, existing methods are still prohibitively expensive for large road networks. Two main reasons are (i) that they fail to utilize the special properties of road networks and (ii) that most of them process queries without indices; the few existing indices consume large amounts of memory and yet have limited effectiveness in reducing query costs. Motivated by this, we propose COLA, the first practical solution for approximate CSP processing on large road networks. COLA exploits the facts that a road network can be effectively partitioned, and that there exists a relatively small set of landmark vertices that commonly appear in CSP results. Accordingly, COLA indexes the vertices lying on partition boundaries, and applies an on-the-fly algorithm called A-Dijk for path computation within a partition, which effectively prunes paths based on landmarks. Extensive experiments demonstrate that on continent-sized road networks, COLA answers an approximate CSP query in sub-second time, whereas existing methods take hours. Interestingly, even without an index, the A-Dijk algorithm in COLA still outperforms previous solutions by more than an order of magnitude.

AB - In a constrained shortest path (CSP) query, each edge in the road network is associated with both a length and a cost. Given an origin s, a destination t, and a cost constraint 9, the goal is to find the shortest path from s to t whose total cost does not exceed 9. Because exact CSP is NP-hard, previous work mostly focuses on approximate solutions. Even so, existing methods are still prohibitively expensive for large road networks. Two main reasons are (i) that they fail to utilize the special properties of road networks and (ii) that most of them process queries without indices; the few existing indices consume large amounts of memory and yet have limited effectiveness in reducing query costs. Motivated by this, we propose COLA, the first practical solution for approximate CSP processing on large road networks. COLA exploits the facts that a road network can be effectively partitioned, and that there exists a relatively small set of landmark vertices that commonly appear in CSP results. Accordingly, COLA indexes the vertices lying on partition boundaries, and applies an on-the-fly algorithm called A-Dijk for path computation within a partition, which effectively prunes paths based on landmarks. Extensive experiments demonstrate that on continent-sized road networks, COLA answers an approximate CSP query in sub-second time, whereas existing methods take hours. Interestingly, even without an index, the A-Dijk algorithm in COLA still outperforms previous solutions by more than an order of magnitude.

UR - http://www.scopus.com/inward/record.url?scp=85020403591&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85020403591&partnerID=8YFLogxK

U2 - 10.14778/3015274.3015277

DO - 10.14778/3015274.3015277

M3 - Conference article

AN - SCOPUS:85020403591

VL - 10

SP - 61

EP - 72

JO - Proceedings of the VLDB Endowment

JF - Proceedings of the VLDB Endowment

SN - 2150-8097

IS - 2

ER -