scholarly journals Cascading Failure Model for Command and Control Networks Based on an m-Order Adjacency Matrix

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yun-ming Wang ◽  
Bo Chen ◽  
Xiao-shuang Chen ◽  
Xiu-e Gao
Keyword(s):  
Adjacency Matrix ◽  
Command And Control ◽  
Cascading Failure ◽  
Model Parameters ◽  
Failure Model ◽  
Nonlinear Load ◽  
New Model ◽  
Control Networks ◽  
Initial Load ◽  
And Control

Cascading failure models for command and control networks (C2 networks) continue to be a challenging and important research area. Current solutions share a common limitation because the solutions focus only on the importance of each node in isolation using one index rather than considering the contribution degree of neighboring nodes, which makes the initial load definition inaccurate and affects the cascading invulnerability of the network. To address this limitation, a new cascading failure model for C2 networks is proposed. The new model CFMAdjM, which is based on an m-order adjacency matrix, proposes a method of initial load definition using the contribution degree of m-order neighboring nodes and defines the nonlinear load capacity model according to the nonlinear relationship between load and capacity. Finally, the influence of model parameters on the cascading failure of C2 networks is analyzed through simulation, and the results demonstrate that the new model effectively resists the cascading failure and enhances the survivability of the network by defining the initial load and adjusting the coefficient appropriately.

scholarly journals A Cascading Failure Model for Command and Control Networks with Hierarchy Structure

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Xiue Gao ◽  
Duoping Zhang ◽  
Keqiu Li ◽  
Bo Chen
Keyword(s):  
Command And Control ◽  
Cascading Failure ◽  
Cascading Failures ◽  
Failure Model ◽  
Relational Models ◽  
Control Networks ◽  
Load Redistribution ◽  
Initial Load ◽  
And Control ◽  
The Impact

Cascading failures in the command and control networks (C2 networks) could substantially affect the network invulnerability to some extent. In particular, without considering the characteristics of hierarchy structure, it is quite misleading to employ the existing cascading failure models and effectively analyze the invulnerability of C2 networks. Therefore, a novel cascading failure model for command and control networks with hierarchy structure is proposed in this paper. Firstly, a method of defining the node’s initial load in C2 networks based on hierarchy-degree is proposed. By applying the method, the impact of organizational positions and the degree of the node on its initial load could be highlighted. Secondly, a nonuniform adjustable load redistribution strategy (NALR strategy) is put forward in this paper. More specifically, adjusting the redistribution coefficient could allocate the load from failure nodes to the higher and the same level neighboring nodes according to different proportions. It could be demonstrated by simulation results that the robustness of C2 networks against cascading failures could be dramatically improved by adjusting the initial load adjustment coefficient, the tolerance parameter, and the load redistribution coefficient. And finally, comparisons with other relational models are provided to verify the rationality and effectiveness of the model proposed in this paper. Subsequently, the invulnerability of C2 networks could be enhanced.

Cascading failure model for improving the robustness of scale-free networks

2018 ◽  
Vol 29 (06) ◽  
pp. 1850044 ◽  
Author(s):  
Zhichao Ju ◽  
Jinlong Ma ◽  
Jianjun Xie ◽  
Zhaohui Qi
Keyword(s):  
Real Life ◽  
Cascading Failure ◽  
Edge Weight ◽  
Failure Model ◽  
Threshold Parameter ◽  
Connected Component ◽  
New Model ◽  
Scale Free ◽  
Small Load ◽  
Scale Free Networks

To control the spread of cascading failure on scale-free networks, we propose a new model with the betweenness centrality and the degrees of the nodes which are combined. The effects of the parameters of the edge weight on cascading dynamics are investigated. Five metrics to evaluate the robustness of the network are given: the threshold parameter ([Formula: see text]), the proportion of collapsed edges ([Formula: see text]), the proportion of collapsed nodes ([Formula: see text]), the number of nodes in the largest connected component ([Formula: see text]) and the number of the connected component ([Formula: see text]). Compared with the degrees of nodes’ model and the betweenness of the nodes’ model, the new model could control the spread of cascading failure more significantly. This work might be helpful for preventing and mitigating cascading failure in real life, especially for small load networks.

scholarly journals Design and Analysis of Collaborative Unmanned Surface-Aerial Vehicle Cruise Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Man Zhu ◽  
Yuan-Qiao Wen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Command And Control ◽  
Collaborative Model ◽  
Weighting Method ◽  
Unmanned Surface Vehicle ◽  
Control Networks ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
And Control

With the increasing application of unmanned surface vehicle-unmanned aerial vehicles (USV-UAVs) in maritime supervision, research on their deployment and control is becoming vitally important. We investigate the application of USV-UAVs for synergistic cruising and evaluate the effectiveness of the proposed collaborative model. First, we build a collaborative model consisting of the cruise vehicles and communication, detection, and command-and-control networks for the USV-UAV. Second, based on an analysis of the problems faced by collaborative USV-UAV systems, we establish a model to evaluate the effectiveness of such synergistic cruises. Third, we propose a weighting method for each evaluation factor. Finally, a model consisting of one UAV and four USVs is employed to validate our synergistic cruise model.

scholarly journals THE INTRODUCTION OF NET-PLATFORM-CENTRIC WARFARE IN THE CHINESE ARMY (PLA)

2021 ◽  
pp. 185-203
Author(s):  
Artsrun Hovhannisyan
Keyword(s):  
Secure Communication ◽  
Common Knowledge ◽  
Command And Control ◽  
The Philippines ◽  
High Rate ◽  
American Military ◽  
Control Networks ◽  
The Us ◽  
The Usa ◽  
And Control

It is no surprise that just like the previous years, this year as well China has expanded its military budget, put another ship to sea, demonstrated new weaponary at the military parade, etc. For the last two decades, all the combat arms of the Chinese army has been developing at a high rate. Many authors claim very specific reasons for the Chinese armaments especially highlighting the conflicts with its immediate neighbors. From a geopolitical point of view, an interesting balance of power is being formed in the East. It’s been several years now that there are some precise problems in China-Japan conflict related to the power over some islands. China actively builds artificial islands which can serve as military bases far away from its shores approximately at an operative depth. And this matter deeply concerns the Philippines and Vietnam. In this light, it would be very interesting to study the balance of forces in the region and to analyze the American military doctrine on the one hand and the Chinese specific military and military-political attempts to appose it on the other hand. It is common knowledge that in political and professional circles in the USA are concerned about the actions and capabilities of China and Russia, which can considerably restrict the US access to key regions of Eurasia: Today, China and Russia have great potential to influence on the traditional American Net-platform weaponary, Air Forces, Navy, command and control networks, and even the orbital groupings. The two countries mentioned above, which are perceived as potential adversaries in the USA, strive to reach the level of the American military by all possible means and develop powerful techonologies. Russia and especially China are designing powerful satellite systems, various long-range missiles, fighter jets, UAVs, etc. New Electronic Warfare (EW) systems are being developed, to suppress or weaken the command and management systems of the US or its allies. The People’s Liberation Army (PLA) of China also has the capacity to destroy settelites, disrupt extraterrestrial intelligence, wreck command and control networks, etc. According to experts, there is no guarantee that the armed forces of the USA can ensure reliable and secure communication and conncetion during conflicts on the theater of military operations, in particular on operational and strategic levels.

scholarly journals Influential Node Identification in Command and Control Networks Based on Integral k-Shell

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Yunming Wang ◽  
Bo Chen ◽  
Weidong Li ◽  
Duoping Zhang
Keyword(s):  
Network Performance ◽  
Simulation Analysis ◽  
Command And Control ◽  
Control Network ◽  
Control Networks ◽  
Influential Nodes ◽  
Influential Node ◽  
And Control ◽  
Global And Local ◽  
The Impact

Influential nodes act as a hub for information transmission in a command and control network. The identification of influential nodes in a network of this nature is a significant and challenging task; however, it is necessary if the invulnerability of the network is to be increased. The existing k-shell method is problematic in that it features a coarse sorting granularity and does not consider the local centrality of nodes. Thus, the degree of accuracy with which the influential nodes can be identified is relatively low. This motivates us to propose a method based on an integral k-shell to identify the influential nodes in a command and control network. This new method takes both the global and local information of nodes into account, introduces the historical k-shell and a 2-order neighboring degree, and refines the k-shell decomposition process in a network. Simulation analysis is carried out from two perspectives: to determine the impact on network performance when influential nodes are removed and to obtain the correlation between the integral k-shell value and its propagation value. The simulation results show that the integral k-shell method, which employs an algorithm of lower complexity, accurately identifies the influence of those nodes with the same k-shell values. Furthermore, the method significantly improves the accuracy with which the influential nodes can be identified.

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