title: Ongoing Processes in a Fitness Network Model under Restricted Resources.
abstract: In real networks, the resources that make up the nodes and edges are finite. This constraint poses a serious problem for network modeling, namely, the compatibility between robustness and efficiency. However, these concepts are generally in conflict with each other. In this study, we propose a new fitness-driven network model for finite resources. In our model, each individual has its own fitness, which it tries to increase. The main assumption in fitness-driven networks is that incomplete estimation of fitness results in a dynamical growing network. By taking into account these internal dynamics, nodes and edges emerge as a result of exchanges between finite resources. We show that our network model exhibits exponential distributions in the in- and out-degree distributions and a power law distribution of edge weights. Furthermore, our network model resolves the trade-off relationship between robustness and efficiency. Our result suggests that growing and anti-growing networks are the result of resolving the trade-off problem itself.
authors.affiliation: Faculty of Engineering, Information and Systems, Tsukuba University, Tsukuba, Ibaraki, Japan.
authors.forename: Takayuki
authors.initials: T
authors.lastname: Niizato
authors.affiliation: School of Fundamental Science and Engineering, Waseda University, Tokyo, Japan.
authors.forename: Yukio-Pegio
authors.initials: YP
authors.lastname: Gunji
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D008962:Models, Theoretical; D013223:Statistics as Topic