Network Analysis: Methodological Foundations (Lecture Notes in Computer Science)
Network Analysis: Methodological Foundations (Lecture Notes in Computer Science)
Social network analysis for routing in disconnected delay-tolerant MANETs
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Minimizing Effective Resistance of a Graph
SIAM Review
Comparison of network criticality, algebraic connectivity, and other graph metrics
Proceedings of the 1st Annual Workshop on Simplifying Complex Network for Practitioners
An open source traffic engineering toolbox
Computer Communications
Error scaling laws for linear optimal estimation from relative measurements
IEEE Transactions on Information Theory
Routing betweenness centrality
Journal of the ACM (JACM)
Autonomic traffic engineering for network robustness
IEEE Journal on Selected Areas in Communications
On random walks in direction-aware network problems
ACM SIGMETRICS Performance Evaluation Review
Robust network planning in nonuniform traffic scenarios
Computer Communications
Bio-inspired strategy for control of viral spreading in networks
Proceedings of the 2nd ACM international conference on High confidence networked systems
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In this article we report on applications and extensions of weighted graph theory in the design and control of communication networks. We model the communication network as a weighted graph and use the existing literature in graph theory to study its behavior. We are particularly interested in the notions of betweenness centrality and resistance distance in the context of communication networks. We argue that in their most general form, the problems in a communication network can be converted to either the optimal selection of weights or optimal selection of paths based on the present values of weights in a graph. Motivated by this, we propose a two-loop general architecture for the control of networks and provide directions to design appropriate control algorithms in each control loop. We show that the total resistance distance (network criticality) of a graph has very useful interpretations in the context of communication networks; therefore, we propose to use network criticality as the main objective function, and we provide guidelines to design the control loops to minimize network criticality. We also discuss the development of new directed weighted graph models and their application to communication networks.