scholarly journals Recent Advances of Percolation Theory in Complex Networks

2018 ◽  
Vol 73 (2) ◽  
pp. 152-164 ◽  
Author(s):  
Deokjae Lee ◽  
B. Kahng ◽  
Y. S. Cho ◽  
K.-I. Goh ◽  
D.-S. Lee
Keyword(s):  
Complex Networks ◽  
Percolation Theory ◽  
Recent Advances

scholarly journals Recent Advances in Complex Networks Theories with Applications

2014 ◽  
Vol 2014 ◽  
pp. 1-4 ◽  
Author(s):  
Hamid Reza Karimi ◽  
Wei Zhang ◽  
Xuebo Yang ◽  
Zhandong Yu
Keyword(s):  
Complex Networks ◽  
Recent Advances

ON SOME RECENT ADVANCES IN COMPLEX SOFTWARE NETWORKS: MODELING, ANALYSIS, EVOLUTION AND APPLICATIONS

2012 ◽  
Vol 22 (02) ◽  
pp. 1250024 ◽  
Author(s):  
HONGCHUN WANG ◽  
KEQING HE ◽  
BING LI ◽  
JINHU LÜ
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Point Of View ◽  
Future Research ◽  
Software Systems ◽  
Recent Advances ◽  
Modeling Analysis ◽  
Real World Applications

Complex software networks, as a typical kind of man-made complex networks, have attracted more and more attention from various fields of science and engineering over the past ten years. With the dramatic increase of scale and complexity of software systems, it is essential to develop a systematic approach to further investigate the complex software systems by using the theories and methods of complex networks and complex adaptive systems. This paper attempts to briefly review some recent advances in complex software networks and also develop some novel tools to further analyze complex software networks, including modeling, analysis, evolution, measurement, and some potential real-world applications. More precisely, this paper first describes some effective modeling approaches for characterizing various complex software systems. Based on the above theoretical and practical models, this paper introduces some recent advances in analyzing the static and dynamical behaviors of complex software networks. It is then followed by some further discussions on potential real-world applications of complex software networks. Finally, this paper outlooks some future research topics from an engineering point of view.

scholarly journals Immunization of Cooperative Spreading Dynamics on Complex Networks

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Jun Wang ◽  
Shi-Min Cai ◽  
Tao Zhou
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Percolation Theory ◽  
Large Degree ◽  
Transmission Probability ◽  
Final State ◽  
The Monte Carlo Method ◽  
Spreading Dynamics ◽  
Opposite Situation ◽  
The Cost

Cooperative spreading dynamics on complex networks is a hot topic in the field of network science. In this paper, we propose a strategy to immunize some nodes based on their degrees. The immunized nodes disable the synergistic effect of cooperative spreading dynamics. We also develop a generalized percolation theory to study the final state of the spreading dynamics. By using the Monte Carlo method, numerical simulations reveal that immunizing nodes with a large degree cannot always be beneficial for containing cooperative spreading. For small values of transmission probability, immunizing hubs can suppress the spreading, while the opposite situation happens for large values of transmission probability. Furthermore, numerical simulations show that immunizing hubs increase the cost of the system. Finally, all numerical simulations can be well predicted by the generalized percolation theory.

scholarly journals IEEE Access Special Section Editorial: Recent Advances on Hybrid Complex Networks: Analysis and Control

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 95083-95086
Author(s):  
Jianquan Lu ◽  
Daniel W. C. Ho ◽  
Tingwen Huang ◽  
Jurgen Kurths ◽  
Ljiljana Trajkovic
Keyword(s):  
Complex Networks ◽  
Special Section ◽  
Recent Advances ◽  
Hybrid Complex ◽  
Networks Analysis ◽  
And Control

scholarly journals Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations

2016 ◽  
Author(s):  
David Koslicki ◽  
Mark Novak
Keyword(s):  
Complex Networks ◽  
Network Topology ◽  
Network Dynamics ◽  
Ecological Networks ◽  
Primary Result ◽  
Qualitative Modeling ◽  
Expected Number ◽  
Recent Advances ◽  
Modeling Techniques

AbstractWe consider the goal of predicting how complex networks respond to chronic (press) perturbations when characterizations of their network topology and interaction strengths are associated with uncertainty. Our primary result is the derivation of exact formulas for the expected number and probability of qualitatively incorrect predictions about a system’s responses under uncertainties drawn form arbitrary distributions of error. These formulas obviate the current use of simulations, algorithms, and qualitative modeling techniques. Additional indices provide new tools for identifying which links in a network are most qualitatively and quantitatively sensitive to error, and for determining the volume of errors within which predictions will remain qualitatively determinate (i.e. sign insensitive). Together with recent advances in the empirical characterization of uncertainty in ecological networks, these tools bridge a way towards probabilistic predictions of network dynamics.

Synchronization in complex networks and its application – A survey of recent advances and challenges

2014 ◽  
Vol 38 (2) ◽  
pp. 184-198 ◽  
Author(s):  
Yang Tang ◽  
Feng Qian ◽  
Huijun Gao ◽  
Jürgen Kurths
Keyword(s):  
Complex Networks ◽  
Recent Advances
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