Modeling and Simulation for Complex Network Based Military System-of-Systems (SoS)

2011 ◽  
Vol 145 ◽  
pp. 224-228 ◽  
Author(s):  
Xiao Song ◽  
Bing Cheng Liu ◽  
Guang Hong Gong
Keyword(s):  
Modeling And Simulation ◽  
Complex Network ◽  
Network Topology ◽  
Network Theory ◽  
Small World ◽  
System Of Systems ◽  
Statistical Parameters ◽  
Complex Network Theory ◽  
Scale Free ◽  
Topology Model

Military SoS increasingly shows its relation of complex network. According to complex network theory, we construct a SoS network topology model for network warfare simulation. Analyzing statistical parameters of the model, it is concluded that the topology model has small-world, high-aggregation and scale-free properties. Based on this model we mainly simulate and analyze vulnerability of the network. And this provides basis for analysis of the robustness and vulnerability of real battle SoS network.

scholarly journals Complex network theory, streamflow, and hydrometric monitoring system design

2015 ◽  
Vol 19 (7) ◽  
pp. 3301-3318 ◽  
Author(s):  
M. J. Halverson ◽  
S. W. Fleming
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Small World ◽  
Detection Algorithm ◽  
Clustering Coefficient ◽  
Network Stability ◽  
Meteorological Forcing ◽  
Complex Network Theory ◽  
Scale Free ◽  
Seasonal Flow

Abstract. Network theory is applied to an array of streamflow gauges located in the Coast Mountains of British Columbia (BC) and Yukon, Canada. The goal of the analysis is to assess whether insights from this branch of mathematical graph theory can be meaningfully applied to hydrometric data, and, more specifically, whether it may help guide decisions concerning stream gauge placement so that the full complexity of the regional hydrology is efficiently captured. The streamflow data, when represented as a complex network, have a global clustering coefficient and average shortest path length consistent with small-world networks, which are a class of stable and efficient networks common in nature, but the observed degree distribution did not clearly indicate a scale-free network. Stability helps ensure that the network is robust to the loss of nodes; in the context of a streamflow network, stability is interpreted as insensitivity to station removal at random. Community structure is also evident in the streamflow network. A network theoretic community detection algorithm identified separate communities, each of which appears to be defined by the combination of its median seasonal flow regime (pluvial, nival, hybrid, or glacial, which in this region in turn mainly reflects basin elevation) and geographic proximity to other communities (reflecting shared or different daily meteorological forcing). Furthermore, betweenness analyses suggest a handful of key stations which serve as bridges between communities and might be highly valued. We propose that an idealized sampling network should sample high-betweenness stations, small-membership communities which are by definition rare or undersampled relative to other communities, and index stations having large numbers of intracommunity links, while retaining some degree of redundancy to maintain network robustness.

Design of the Small World Model by NS2

2014 ◽  
Vol 496-500 ◽  
pp. 2338-2341
Author(s):  
Jun Shang ◽  
Hao Qiang Liu ◽  
Qiang Liu ◽  
Zi Qi Liu
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Applied Research ◽  
Lower Cost ◽  
Small World ◽  
Scale Free Network ◽  
World Model ◽  
Complex Network Theory ◽  
Scale Free ◽  
Free Network

WSN is the network which is used mostly in the world nowadays, and it has the characteristics that lower cost and better functions than other kinds of the network, and the WSN network is built by the ordinary nodes and the super nodes.Theoretical study of the complex network is widely involved in the fields of computer networks, and the applied research becomes more and more important in the future. It has caused many academic attention about how to apply the complex network theory among the specific application in recent years. In the complex network theory, there has been a number of important research results about the use of the small-world network, scale-free network in the field of transportation.

Research on the Structure of Peer-to-Peer Overlay Based on the Complex Network Theory

2012 ◽  
Vol 263-266 ◽  
pp. 1096-1099
Author(s):  
Zhi Yong Jiang
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Degree Distribution ◽  
Path Length ◽  
Small World ◽  
Peer To Peer ◽  
Clustering Coefficient ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
The Mean

Relationship between nodes in peer-to-peer overlay, currently becomes a hot topic in the field of complex network. In this paper a model of peer-to-peer overlay was purposed. And then the paper focused on figuring out the mean-shortest path length (MSPL), clustering coefficient (CC) and the degree of every node which allowed us to discover the degree distribution. The results show that the degree distribution function follows approximately power law distribution and the network possesses notable clustering and small-world properties.

scholarly journals Small-World and Scale-Free Network Models for IoT Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Insoo Sohn
Keyword(s):  
Graph Theory ◽  
Complex Network ◽  
Network Topology ◽  
Network Models ◽  
Small World ◽  
Small World Networks ◽  
Scale Free ◽  
Scale Free Networks ◽  
Massive Number ◽  
Complex Network Models

It is expected that Internet of Things (IoT) revolution will enable new solutions and business for consumers and entrepreneurs by connecting billions of physical world devices with varying capabilities. However, for successful realization of IoT, challenges such as heterogeneous connectivity, ubiquitous coverage, reduced network and device complexity, enhanced power savings, and enhanced resource management have to be solved. All these challenges are heavily impacted by the IoT network topology supported by massive number of connected devices. Small-world networks and scale-free networks are important complex network models with massive number of nodes and have been actively used to study the network topology of brain networks, social networks, and wireless networks. These models, also, have been applied to IoT networks to enhance synchronization, error tolerance, and more. However, due to interdisciplinary nature of the network science, with heavy emphasis on graph theory, it is not easy to study the various tools provided by complex network models. Therefore, in this paper, we attempt to introduce basic concepts of graph theory, including small-world networks and scale-free networks, and provide system models that can be easily implemented to be used as a powerful tool in solving various research problems related to IoT.

Selection Method of Customer Partners in Customer Collaborative Product Innovation

2014 ◽  
Vol 23 (4) ◽  
pp. 423-435 ◽  
Author(s):  
Fei Li ◽  
Yu Yang ◽  
Jianzhong Xie ◽  
Aijun Liu ◽  
Qian Chen
Keyword(s):  
Complex Network ◽  
Product Innovation ◽  
Online Community ◽  
Innovation Process ◽  
Partner Selection ◽  
Small World ◽  
Selection Method ◽  
Network Efficiency ◽  
Complex Network Theory ◽  
Scale Free

AbstractPartner selection is an important aspect of the customer collaborative product innovation process and aims to select innovative customer partners from huge numbers of customers, fast and accurately. The purpose of this article is to present a quantitative partner selection method based on the complex network theory. In this method, the complex network model of the Online Community Customer Network (OCCN) is constructed, and network centrality is used as the initial index of customer partner selection. Then, network efficiency and delta centrality are used to evaluate the effect of the index. An example is presented to reflect the feasibility and efficiency of the proposed method. Results validate the small-world and scale-free properties of the OCCN and show that betweenness centrality is the most appropriate index for partner selection in the OCCN.

scholarly journals Propagation Laws of Reclamation Risk in Tailings Ponds Using Complex Network Theory

Metals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1789
Author(s):  
Zhixin Zhen ◽  
Ying Zhang ◽  
Mengrong Hu
Keyword(s):  
Complex Network ◽  
Network Theory ◽  
Three Dimensional ◽  
Mining Industry ◽  
Small World ◽  
Statistical Characteristics ◽  
Accident Risk ◽  
Complex Network Theory ◽  
Tailings Pond ◽  
Tailings Ponds

Accidents have occurred periodically in the tailings ponds where mine solid waste is stored in recent years, and thus their safety has become one of the constraints restricting the sustainable development of the mining industry. Reclamation is an important way to treat tailings ponds, but improper reclamation methods and measures not only cannot reduce the accident risk of tailings ponds, but will further increase the pollution to the surrounding environment. The influencing factors of reclamation accidents in tailings ponds are complex, and the existing models cannot characterize them. In order to study the propagation process of tailings pond reclamation risk, this paper proposes a three-dimensional identification framework for accident hazards based on evidence (TDIFAHE) to identify all potential hazards that may occur during the reclamation stage, and obtain a list of hazards. Based on the complex network theory, this paper uses identified hazards as network nodes and the correlation between hazards as the edges of the network. Based on the identified hazard data, the evolution network of reclamation risk in tailings ponds (ENRRTP) is constructed. By analyzing the statistical characteristics of ENRRTP, it can be found that ENRRTP has small world and scale-free characteristics. The above characteristics show that the reclamation risk of tailings ponds is coupled with multiple factors and the disaster path is short. Giving priority to those hub hazards that have a dominant impact on the reclamation risk can significantly reduce the reclamation risk of the tailings pond.

scholarly journals Double Push Strategy of Knowledge for Product Design Based on Complex Network Theory

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Xue-rui Li ◽  
Sui-huai Yu ◽  
Jian-jie Chu ◽  
Deng-kai Chen ◽  
Lin-jian Wu
Keyword(s):  
Product Design ◽  
Complex Network ◽  
Network Model ◽  
Network Theory ◽  
Auxiliary Function ◽  
Triangular Fuzzy Number ◽  
Knowledge Network ◽  
Design Knowledge ◽  
Complex Network Theory ◽  
Scale Free

Reasonable application of design knowledge can help improve the efficiency and quality of product design. Based on complex network theory, this study proposes a double push strategy of knowledge for product design. The proposal introduces the concept of attribute similarity and triangular fuzzy number and uses the theory and method of complex network to build the knowledge network model for product design that contains creative knowledge subnetwork and engineering knowledge subnetwork. This paper is to understand the structure and dynamics of the knowledge network model and to identify and predict knowledge nodes and knowledge groups strongly related to design intent in view of the scale-free network topology analysis theory. We develop a double push strategy of product design knowledge to implement the effective auxiliary function for product design process. Finally, a design case of antalgic pump is presented to demonstrate the practicability and validity of the strategy.

A framework for assessing project vulnerability to crises

2019 ◽  
Vol 12 (4) ◽  
pp. 1079-1096 ◽  
Author(s):  
Aimin Wang
Keyword(s):  
Complex Network ◽  
Network Topology ◽  
Network Theory ◽  
Critical Role ◽  
Diffusion Path ◽  
Content Type ◽  
Complex Network Theory ◽  
Systems Perspective ◽  
Project Network

Purpose The purpose of this paper is to propose a framework for assessing the vulnerability of projects to crises. The study seeks to clarify the cascade effects of disruptions leading to project crises and to improve project robustness against crises from a systems perspective. Design/methodology/approach A framework for assessing project vulnerability to crises is developed using complex network theory. The framework includes network representation of project systems, analyzing project network topology, simulating the cascade of unexpected disruptions and assessing project vulnerability. Use of the framework is then illustrated by applying it to a case study of a construction project. Findings Project network topology plays a critical role in resisting crises. By increasing the resilience of the critical tasks and adjusting the structure of a project, the complexity and vulnerability of the project can be reduced, which in turn decreases the occurrence of crises. Research limitations/implications The proposed framework is used in a case study. Further studies of its application to projects in diverse industries would be beneficial to enhance the robustness of the results. Practical implications Project crises can threaten the survival of a project and endanger the organization’s security. The proposed framework helps prevent and mitigate project crises by protecting critical tasks and blocking the diffusion path from a systems perspective. Originality/value This paper presents a novel framework based on complex network theory to assess project vulnerability, which provides a systemic understanding of the cascade of disruptions that lead to project crises.

scholarly journals Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Nai-Ru Xu ◽  
Jia-Bao Liu ◽  
De-Xun Li ◽  
Jun Wang
Keyword(s):  
Supply Chain ◽  
Complex Network ◽  
Network Theory ◽  
Clustering Coefficient ◽  
Supply Chain Network ◽  
Evolutionary Mechanism ◽  
Complex Network Theory ◽  
Scale Free ◽  
Agile Supply Chain ◽  
Network Research

The paper establishes the evolutionary mechanism model of agile supply chain network by means of complex network theory which can be used to describe the growth process of the agile supply chain network and analyze the complexity of the agile supply chain network. After introducing the process and the suitability of taking complex network theory into supply chain network research, the paper applies complex network theory into the agile supply chain network research, analyzes the complexity of agile supply chain network, presents the evolutionary mechanism of agile supply chain network based on complex network theory, and uses Matlab to simulate degree distribution, average path length, clustering coefficient, and node betweenness. Simulation results show that the evolution result displays the scale-free property. It lays the foundations of further research on agile supply chain network based on complex network theory.

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