Geographical networks evolving with optimal policy

Details Geographical networks evolving with optimal policy Geographical networks evolving with optimal policy

2006-05-06

arxiv.org/abs/physics/0605054v3

Physical Review E, 75, 036106 (2007)

Physics

Physics and Society

8 pages, 6 figures

Scientific paper

10.1103/PhysRevE.75.036106

In this article, we propose a growing network model based on an optimal policy involving both topological and geographical measures. In this model, at each time step, a new node, having randomly assigned coordinates in a $1 \times 1$ square, is added and connected to a previously existing node $i$, which minimizes the quantity $r_i^2/k_i^\alpha$, where $r_i$ is the geographical distance, $k_i$ the degree, and $\alpha$ a free parameter. The degree distribution obeys a power-law form when $\alpha=1$, and an exponential form when $\alpha=0$. When $\alpha$ is in the interval $(0,1)$, the network exhibits a stretched exponential distribution. We prove that the average topological distance increases in a logarithmic scale of the network size, indicating the existence of the small-world property. Furthermore, we obtain the geographical edge-length distribution, the total geographical length of all edges, and the average geographical distance of the whole network. Interestingly, we found that the total edge-length will sharply increase when $\alpha$ exceeds the critical value $\alpha_c=1$, and the average geographical distance has an upper bound independent of the network size. All the results are obtained analytically with some reasonable approximations, which are well verified by simulations.

Affiliated with

Also associated with

No associations

Rating

Geographical networks evolving with optimal policy does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Geographical networks evolving with optimal policy, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Geographical networks evolving with optimal policy will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-81382