Improving network robustness by edge modification

  title={Improving network robustness by edge modification},
  author={Alina Beygelzimer and Geoffrey Grinstein and Ralph Linsker and Irina Rish},
  journal={Physica A-statistical Mechanics and Its Applications},

Figures from this paper

Improving network robustness

A simple, fully decentralized approach to improving robustness of existing unstructured overlay networks against a selective deletion of nodes by computing the curve governing the tradeoff between the number of modifications and the increase in robustness.

On local link repairing in complex communication networks under intentional attack

  • Shi XiaoGaoxi Xiao
  • Computer Science
    2007 6th International Conference on Information, Communications & Signal Processing
  • 2007
This paper proposes and evaluates a simple local link repairing strategy, the main idea is to restore some of the links that have been cut when a network node is crashed by rewiring each of them to another node.

Robustness of Complex Communication Networks under Rewiring Operations

It is shown that different scale-free networks with exactly the same degree of every node can have different tolerances to the intentional attack, demonstrating that nodal-degree distribution does not define network robustness solely by itself.

Assessing and Altering Robustness of Large Graphs

This work critically analyze a diverse list of proposed robustness measures and identifies their strengths and weaknesses in quantifying graph robustness, and formulate three graph manipulation problems involving node and edge deletions to degrade, and edge additions to improve the robustness of a given graph as defined by its natural connectivity.

Increase or Decrease Network Robustness with Genetic algorithms : A method for maximization or minimization of network robustness in attack or random failure scenarios

This paper presents a method to increase the attack impact or decrease random failure impact on the network depending on the purpose, and uses genetic algorithm as an optimization approach for improving network robustness measurement function.

Enhancing the Robustness and Efficiency of Scale-free Network with Limited Link Addition

It is shown that network topology reconfiguration optimization with limited link addition (NTRLA) problem is NP-hard and a preferential configuration node-protecting cycle method is developed to do trade-off between network robustness and efficiency.

Improving the robustness of scale-free networks by maintaining community structure

A preferential rewiring method to improve network robustness which not only keeps degree distribution unchanged but also preserves community structure and decreases the number of rewired edges at the same time is proposed.

Adding links on minimum degree and longest distance strategies for improving network robustness and efficiency

Through numerical simulation, it is found that the robustness is effectively improved by adding links on the minimum degree strategy for both synthetic trees and real networks.

Interactive Visualization of Robustness Enhancement in Scale-free Networks with Limited Edge Addition (RENEA)

It is concluded that applying RENEA on a scale-free network while interacting with the user can significantly improve its attack survivability at the highest level.



Robustness and Vulnerability of Scale-Free Random Graphs

It is shown that the LCD graph is much more robust than classical random graphs with the same number of edges, but also more vulnerable to attack, namely robustness to random damage, and vulnerability to malicious attack.

Error and attack tolerance of complex networks

It is found that scale-free networks, which include the World-Wide Web, the Internet, social networks and cells, display an unexpected degree of robustness, the ability of their nodes to communicate being unaffected even by unrealistically high failure rates.

2-Peak and 3-Peak Optimal Complex Networks

It is proved analytically that the optimal network configuration under a classic measure of robustness is altogether different from both the power-law node connectivity distribution and the exponentially decaying connectivity distribution: in all cases, failure and/or attack, there are no more than three distinct node connectivities in the optimalnetwork.

Breakdown of the internet under intentional attack.

It is argued that, near criticality, the average distance between sites in the spanning (largest) cluster scales with its mass, M, as square root of [M], rather than as log (k)M, as expected for random networks away from criticality.

Emergence of scaling in random networks

A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.

Resilience of the internet to random breakdowns

This work shows analytically and numerically that for alpha</=3 the transition never takes place, unless the network is finite, and finds that the physical structure of the Internet is impressively robust, with p(c)>0.99.

Random walks in peer-to-peer networks

It is shown that samples taken from consecutive steps of a random walk can achieve statistical properties similar to independent sampling if the second eigenvalue of the transition matrix is hounded away from 1, which translates to good expansion of the network.

Network topology generators: degree-based vs. structural

It is found that network generators based on the degree distribution more accurately capture the large-scale structure of measured topologies, and an explanation is sought by examining the nature of hierarchy in the Internet more closely.

The degree sequence of a scale‐free random graph process

Here the authors obtain P(d) asymptotically for all d≤n1/15, where n is the number of vertices, proving as a consequence that γ=3.9±0.1 is obtained.

Distributed construction of random expander networks

  • Ching LawK. Siu
  • Computer Science
    IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428)
  • 2003
A novel distributed algorithm for constructing random overlay networks that are composed of d Hamilton cycles is presented and is robust against an offline adversary selecting the sequence of the join and leave operations.