Analysis of Average Shortest-Path Length of Scale-Free Network

Computing the average shortest-path length of a large scale-free network needs much memory space and computation time. Hence, parallel computing must be applied. In order to solve the load-balancing problem for coarse-grained parallelization, the relationship between the computing time of a single-s...

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Main Authors: Guoyong Mao, Ning Zhang
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2013/865643
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author Guoyong Mao
Ning Zhang
author_facet Guoyong Mao
Ning Zhang
author_sort Guoyong Mao
collection DOAJ
description Computing the average shortest-path length of a large scale-free network needs much memory space and computation time. Hence, parallel computing must be applied. In order to solve the load-balancing problem for coarse-grained parallelization, the relationship between the computing time of a single-source shortest-path length of node and the features of node is studied. We present a dynamic programming model using the average outdegree of neighboring nodes of different levels as the variable and the minimum time difference as the target. The coefficients are determined on time measurable networks. A native array and multimap representation of network are presented to reduce the memory consumption of the network such that large networks can still be loaded into the memory of each computing core. The simplified load-balancing model is applied on a network of tens of millions of nodes. Our experiment shows that this model can solve the load-imbalance problem of large scale-free network very well. Also, the characteristic of this model can meet the requirements of networks with ever-increasing complexity and scale.
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spelling doaj-art-367cc30388de47da809b5e96859f20c52025-02-03T07:25:30ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/865643865643Analysis of Average Shortest-Path Length of Scale-Free NetworkGuoyong Mao0Ning Zhang1Department of Electronic Information and Electric Engineering, Changzhou Institute of Technology, Changzhou 213002, ChinaBusiness School, University of Shanghai for Science and Technology, Shanghai 200093, ChinaComputing the average shortest-path length of a large scale-free network needs much memory space and computation time. Hence, parallel computing must be applied. In order to solve the load-balancing problem for coarse-grained parallelization, the relationship between the computing time of a single-source shortest-path length of node and the features of node is studied. We present a dynamic programming model using the average outdegree of neighboring nodes of different levels as the variable and the minimum time difference as the target. The coefficients are determined on time measurable networks. A native array and multimap representation of network are presented to reduce the memory consumption of the network such that large networks can still be loaded into the memory of each computing core. The simplified load-balancing model is applied on a network of tens of millions of nodes. Our experiment shows that this model can solve the load-imbalance problem of large scale-free network very well. Also, the characteristic of this model can meet the requirements of networks with ever-increasing complexity and scale.http://dx.doi.org/10.1155/2013/865643
spellingShingle Guoyong Mao
Ning Zhang
Analysis of Average Shortest-Path Length of Scale-Free Network
Journal of Applied Mathematics
title Analysis of Average Shortest-Path Length of Scale-Free Network
title_full Analysis of Average Shortest-Path Length of Scale-Free Network
title_fullStr Analysis of Average Shortest-Path Length of Scale-Free Network
title_full_unstemmed Analysis of Average Shortest-Path Length of Scale-Free Network
title_short Analysis of Average Shortest-Path Length of Scale-Free Network
title_sort analysis of average shortest path length of scale free network
url http://dx.doi.org/10.1155/2013/865643
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