On power-law relationships of the Internet topology
Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
A random graph model for massive graphs
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Network topology generators: degree-based vs. structural
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
BRITE: An Approach to Universal Topology Generation
MASCOTS '01 Proceedings of the Ninth International Symposium in Modeling, Analysis and Simulation of Computer and Telecommunication Systems
A first-principles approach to understanding the internet's router-level topology
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Comparing the Structure of Power-Law Graphs and the Internet AS Graph
ICNP '04 Proceedings of the 12th IEEE International Conference on Network Protocols
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
Orbis: rescaling degree correlations to generate annotated internet topologies
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
ACOS'07 Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6
A systematic method for network topology reconfiguration with limited link additions
Journal of Network and Computer Applications
| Hi-index | 0.00 |
Recent studies have described the topologies of various networks including the Internet are categorized as scale-free networks. Scale-free network is extremely vulnerable to node attacks. However, the suitability of the topology of the Internet for communications has not been studied. We investigate whether the current Internet is optimized in both aspects of communication efficiency and attack tolerance. For this, we define three metrics to represent the capabilities of the network, which are Clustering coefficient, Efficiency, and Reachability. As a result, we found that the value of 驴, a scaling exponent in power law function representing the degree distribution of a scale-free network, may be reduced in the present Internet. To reduce the value of 驴, we propose four strategies for re-organizing a network. However, in real network, we cannot control the user's preference directly. We use a diffusion model based on social behavior dynamics. Furthermore, we show the characteristics of the re-organized networks, and discuss which strategy is more appropriate for achieving a desired network.