2014Unpublished venueRequires access

SNAM: A heterogeneous complex networks generation model

Bassant E. Youssef, Mohamed R. M. Rizk

Open publisher page 5 citations

Abstract

Complex networks are found in various fields. Complex networks are characterized by having a scale-free power-law degree distribution, a small average path length (small world phenomenon), a high average clustering coefficient, and showing the emergence of community structure. Most proposed complex networks models did not incorporate all of these four statistical properties of complex networks. Additionally, models have also neglected incorporating the heterogeneous nature of network nodes. Moreover, even proposed heterogeneous complex network models were not general for different complex networks. Here, we define a new aspect of node-heterogeneity that was never previously considered which is the node connection standard heterogeneity. In this paper, we propose a generation model for heterogeneous complex networks. We introduce our novel model “settling node adaptive model” SNAM. SNAM reflects the heterogeneous nature of nodes' connection-standard requirements. Such novel nodes' connection standard criterion was not included in any previous network generation models. SNAM was successful in preserving the power law degree distribution, the small world phenomenon and the high clustering coefficient of complex networks.

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What this paper is about

Complex networks are found in various fields. Complex networks are characterized by having a scale-free power-law degree distribution, a small average path length (small world phenomenon), a high average clustering coefficient, and showing the emergence of community structure. Most proposed complex networks models did not incorporate all of these four statistical properties of complex networks. Additionally, models have also neglected incorporating the heterogeneous nature of network nodes. Moreover, even proposed heterogeneous complex network models were not general for different complex networks. Here, we define a new aspect of node-heterogeneity that was never previously considered which is the node connection standard heterogeneity. In this paper, we propose a generation model for heterogeneous complex networks. We introduce our novel model “settling node adaptive model” SNAM. SNAM reflects the heterogeneous nature of nodes' connection-standard requirements. Such novel nodes' connection standard criterion was not included in any previous network generation models. SNAM was successful in preserving the power law degree distribution, the small world phenomenon and the high clustering coefficient of complex networks.

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Available abstract

Complex networks are found in various fields. Complex networks are characterized by having a scale-free power-law degree distribution, a small average path length (small world phenomenon), a high average clustering coefficient, and showing the emergence of community structure. Most proposed complex networks models did not incorporate all of these four statistical properties of complex networks. Additionally, models have also neglected incorporating the heterogeneous nature of network nodes. Moreover, even proposed heterogeneous complex network models were not general for different complex networks. Here, we define a new aspect of node-heterogeneity that was never previously considered which is the node connection standard heterogeneity. In this paper, we propose a generation model for heterogeneous complex networks. We introduce our novel model “settling node adaptive model” SNAM. SNAM reflects the heterogeneous nature of nodes' connection-standard requirements. Such novel nodes' connection standard criterion was not included in any previous network generation models. SNAM was successful in preserving the power law degree distribution, the small world phenomenon and the high clustering coefficient of complex networks.

Key concepts: Computer science

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