### Abstract

This paper presents new efficient shortest path algorithms to solve single origin shortest path problems (SOSP problems) and multiple origins shortest path problems (MOSP problems) for hierarchically clustered data networks. To solve an SOSP problem for a network with n nodes, the distributed version of our algorithm reaches the time complexity of O(log(n)), which is less than the time complexity of O(log ^{2}(n)) achieved by the best existing algorithm [1]. To solve an MOSP problem, our algorithm minimizes the needed computation resources, including computation processors and communication links for the computation of each shortest path so that we can achieve massive parallelization. The time complexity of our algorithm for an MOSP problem is O(mlog(n)), which is much less than the time complexity of O(Mlog ^{2}(n)) of the best previous algorithm. Here, M is the number of the shortest paths to be computed and m is a positive number related to the network topology and the distribution of the nodes incurring communications, m is usually much smaller than M. Our experiment shows that m is almost a constant when the network size increases. Accordingly, our algorithm is significantly faster than the best previous algorithms to solve MOSP problems for large data networks.

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

Pages (from-to) | 841-855 |

Number of pages | 15 |

Journal | IEEE Transactions on Parallel and Distributed Systems |

Volume | 9 |

Issue number | 9 |

DOIs | |

Publication status | Published - 1 Dec 1998 |

Externally published | Yes |

### Fingerprint

### Keywords

- Data network
- Distributed computation
- Hierarchical network
- Parallel processing
- Shortest path

### ASJC Scopus subject areas

- Signal Processing
- Hardware and Architecture
- Computational Theory and Mathematics

### Cite this

**A new parallel and distributed shortest path algorithm for hierarchically clustered data networks.** / Zhu, Shan; Huang, Garng Morton.

Research output: Contribution to journal › Article

}

TY - JOUR

T1 - A new parallel and distributed shortest path algorithm for hierarchically clustered data networks

AU - Zhu, Shan

AU - Huang, Garng Morton

PY - 1998/12/1

Y1 - 1998/12/1

N2 - This paper presents new efficient shortest path algorithms to solve single origin shortest path problems (SOSP problems) and multiple origins shortest path problems (MOSP problems) for hierarchically clustered data networks. To solve an SOSP problem for a network with n nodes, the distributed version of our algorithm reaches the time complexity of O(log(n)), which is less than the time complexity of O(log 2(n)) achieved by the best existing algorithm [1]. To solve an MOSP problem, our algorithm minimizes the needed computation resources, including computation processors and communication links for the computation of each shortest path so that we can achieve massive parallelization. The time complexity of our algorithm for an MOSP problem is O(mlog(n)), which is much less than the time complexity of O(Mlog 2(n)) of the best previous algorithm. Here, M is the number of the shortest paths to be computed and m is a positive number related to the network topology and the distribution of the nodes incurring communications, m is usually much smaller than M. Our experiment shows that m is almost a constant when the network size increases. Accordingly, our algorithm is significantly faster than the best previous algorithms to solve MOSP problems for large data networks.

AB - This paper presents new efficient shortest path algorithms to solve single origin shortest path problems (SOSP problems) and multiple origins shortest path problems (MOSP problems) for hierarchically clustered data networks. To solve an SOSP problem for a network with n nodes, the distributed version of our algorithm reaches the time complexity of O(log(n)), which is less than the time complexity of O(log 2(n)) achieved by the best existing algorithm [1]. To solve an MOSP problem, our algorithm minimizes the needed computation resources, including computation processors and communication links for the computation of each shortest path so that we can achieve massive parallelization. The time complexity of our algorithm for an MOSP problem is O(mlog(n)), which is much less than the time complexity of O(Mlog 2(n)) of the best previous algorithm. Here, M is the number of the shortest paths to be computed and m is a positive number related to the network topology and the distribution of the nodes incurring communications, m is usually much smaller than M. Our experiment shows that m is almost a constant when the network size increases. Accordingly, our algorithm is significantly faster than the best previous algorithms to solve MOSP problems for large data networks.

KW - Data network

KW - Distributed computation

KW - Hierarchical network

KW - Parallel processing

KW - Shortest path

UR - http://www.scopus.com/inward/record.url?scp=0032163202&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032163202&partnerID=8YFLogxK

U2 - 10.1109/71.722218

DO - 10.1109/71.722218

M3 - Article

VL - 9

SP - 841

EP - 855

JO - IEEE Transactions on Parallel and Distributed Systems

JF - IEEE Transactions on Parallel and Distributed Systems

SN - 1045-9219

IS - 9

ER -