Modeling Link Weights in Backbone Networks
Abstract
Complex networks have become a large area of study due to their pervasiveness in today's society and our dependence on them. While network science enables engineers and scientists to improve resilience of networks, due to lack of realistic data, simplistic assumptions may result in incorrect conclusions. Network service providers optimize their designs and plan for future capacities based on realistic population estimates. In this paper, we propose two synthetic network models that assign weight to links based on realistic population data of node locations. First, the weighted link model averages the population of cities to assign link weights, whereas the tiered weighted link model assigns preset link weights based on the quartile population that the link weight falls into. We study the performance of model networks under targeted attack scenarios, and our results indicate performance varies based on attack scenario.
Recommended Citation
I. H. Pittwood and E. K. Çetinkaya, "Modeling Link Weights in Backbone Networks," Proceedings of the 9th International Workshop on Resilient Networks Design and Modeling (2017, Alghero, Italy), Institute of Electrical and Electronics Engineers (IEEE), Sep 2017.
The definitive version is available at https://doi.org/10.1109/RNDM.2017.8093021
Meeting Name
9th International Workshop on Resilient Networks Design and Modeling, RNDM 2017 (2017, Sep. 4-6, Alghero, Italy)
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Complex networks; Back-bone network; Betweenness; Connectivity; Link between-ness; Link model; Node strength; Population; Resilience; Weighted graph; Population statistics; Backbone network; Link modeling; Node betweenness
International Standard Book Number (ISBN)
978-1-5386-0671-1
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Sep 2017