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

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24 Citations (Scopus)

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 languageEnglish
Pages (from-to)841-855
Number of pages15
JournalIEEE Transactions on Parallel and Distributed Systems
Volume9
Issue number9
DOIs
Publication statusPublished - 1 Dec 1998
Externally publishedYes

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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

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title = "A new parallel and distributed shortest path algorithm for hierarchically clustered data networks",
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.",
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