TY - JOUR

T1 - Transport between multiple users in complex networks

AU - Carmi, S.

AU - Wu, Z.

AU - López, E.

AU - Havlin, S.

AU - Eugene Stanley, H.

PY - 2007/5

Y1 - 2007/5

N2 - We study the transport properties of model networks such as scale-free and Erdös-Rényi networks as well as a real network. We consider few possibilities for the trnasport problem. We start by studying the conductance G between two arbitrarily chosen nodes where each link has the same unit resistance. Our theoretical analysis for scale-free networks predicts a broad range of values of G, with a power-law tail distribution Φ SF(G) ∼ G -gG, where g G=2λ-1, and λ is the decay exponent for the scale-free network degree distribution. The power-law tail in Φ SF(G) leads to large values of G, thereby significantly improving the transport in scale-free networks, compared to Erdös- Rényi networks where the tail of the conductivity distribution decays exponentially. We develop a simple physical picture of the transport to account for the results. The other model for transport is the max-flow model, where conductance is defined as the number of link-independent paths between the two nodes, and find that a similar picture holds. The effects of distance on the value of conductance are considered for both models, and some differences emerge. We then extend our study to the case of multiple sources ans sinks, where the transport is defined between two groups of nodes. We find a fundamental difference between the two forms of flow when considering the quality of the transport with respect to the number of sources, and find an optimal number of sources, or users, for the max-flow case. A qualitative (and partially quantitative) explanation is also given.

AB - We study the transport properties of model networks such as scale-free and Erdös-Rényi networks as well as a real network. We consider few possibilities for the trnasport problem. We start by studying the conductance G between two arbitrarily chosen nodes where each link has the same unit resistance. Our theoretical analysis for scale-free networks predicts a broad range of values of G, with a power-law tail distribution Φ SF(G) ∼ G -gG, where g G=2λ-1, and λ is the decay exponent for the scale-free network degree distribution. The power-law tail in Φ SF(G) leads to large values of G, thereby significantly improving the transport in scale-free networks, compared to Erdös- Rényi networks where the tail of the conductivity distribution decays exponentially. We develop a simple physical picture of the transport to account for the results. The other model for transport is the max-flow model, where conductance is defined as the number of link-independent paths between the two nodes, and find that a similar picture holds. The effects of distance on the value of conductance are considered for both models, and some differences emerge. We then extend our study to the case of multiple sources ans sinks, where the transport is defined between two groups of nodes. We find a fundamental difference between the two forms of flow when considering the quality of the transport with respect to the number of sources, and find an optimal number of sources, or users, for the max-flow case. A qualitative (and partially quantitative) explanation is also given.

UR - http://www.scopus.com/inward/record.url?scp=34250359141&partnerID=8YFLogxK

U2 - 10.1140/epjb/e2007-00129-0

DO - 10.1140/epjb/e2007-00129-0

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???

AN - SCOPUS:34250359141

SN - 1434-6028

VL - 57

SP - 165

EP - 174

JO - European Physical Journal B

JF - European Physical Journal B

IS - 2

ER -