Network capacity based on complex network theory
Li Wang
Abstract
Li Wang
Abstract
Based on the complex network theory,we present formulae for estimating the maximum of betweenness centrality of edge in a network after the random breakdowns happen.Betweenness centrality of edge is defined as the number of shortest paths traveling through an edge given a communication protocol.The edge possessing the max betweenness tends to be congested in communication process,so providing more precise estimation of edge betweenness can give more exact estimation to the capacity of distributing traffic to a network.Finally,We confirm the formula by simulation analysis.Little attention has been paid to the effect of random breakdown on the edge betweenness,so the proposed formula provides a new solution to estimating edge betweenness and also it can be useful for traffic engineering and network planning.
OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Based on the complex network theory,we present formulae for estimating the maximum of betweenness centrality of edge in a network after the random breakdowns happen.Betweenness centrality of edge is defined as the number of shortest paths traveling through an edge given a communication protocol.The edge possessing the max betweenness tends to be congested in communication process,so providing more precise estimation of edge betweenness can give more exact estimation to the capacity of distributing traffic to a network.Finally,We confirm the formula by simulation analysis.Little attention has been paid to the effect of random breakdown on the edge betweenness,so the proposed formula provides a new solution to estimating edge betweenness and also it can be useful for traffic engineering and network planning.
Key concepts: Betweenness centrality, Enhanced Data Rates for GSM Evolution, Centrality, Computer science, Process (computing), Network theory, Complex network, Network controllability