Critical Nodes Identification: A Non-Cooperative Method for Unknown Topology Information in Ad Hoc Networks

The foundation of ad hoc networks lies in the guarantee of continuous connectivity.However,critical nodes,whose failure can easily destroy network connectivity,will influence the ad hoc network connectivity significantly.To protect the network efficiently,critical nodes should be identified accurately and rapidly.Unlike existing critical node identification methods for unknown topology that identify critical nodes according to historical information,this paper develops a critical node identification method to relax the prior topology information condition about critical nodes.Specifically,we first deduce a theorem about the minimum communication range for a node through the number of nodes and deployment ranges,and prove the universality of the theorem in a realistic two-dimensional scenario.After that,we analyze the relationship between communication range and degree value for each node and prove that the greater number of nodes within the communication range of a node,the greater degree value of nodes with high probability.Moreover,we develop a novel strategy to improve the accuracy of critical node identification without topology information.Finally,simulation results indicate the proposed strategy can achieve high accuracy and low redundancy while ensuring low time consumption in the scenarios with unknown topology information in ad hoc networks.

Identification of critical nodes for cascade faults of grids based on electrical PageRank

In this paper,the electrical PageRank method is proposed to identify the critical nodes in a power grid considering cascading faults as well as directional weighting.This method can rapidly and accurately focus on the critical nodes in the power system.First,the proposed method simulates the scenario in a grid after a node is attacked by cascading faults.The load loss of the grid is calculated.Second,the electrical PageRank algorithm is proposed.The nodal importance of a grid is determined by considering cascading faults as well as directional weights.The electrical PageRank values of the system nodes are obtained based on the proposed electrical PageRank algorithm and ranked to identify the critical nodes in a grid.Finally,the effectiveness of the proposed method is verified using the IEEE39 node system.The proposed method is highly effective in preventing the occurrence of cascading faults in power systems.

Geodesic Vulnerability Approach for Identification of Critical Buses in Power Systems

One of the most critical issues in the evaluation of power systems is the identification of critical buses. For this purpose, this paper proposes a new methodology that evaluates the substitution of the power flow technique by the geodesic vulnerability index to identify critical nodes in power systems.Both methods are applied comparatively to demonstrate the scope of the proposed approach. The applicability of the methodology is illustrated using the IEEE 118-bus test system as a case study. To identify the critical components, a node is initially disconnected, and the performance of the resulting topology is evaluated in the face of simulations for multiple cascading faults. Cascading events are simulated by randomly removing assets on a system that continually changes its structure with the elimination of each component. Thus, the classification of the critical nodes is determined by evaluating the resulting performance of 118 different topologies and calculating the damaged area for each of the disintegration curves of cascading failures. In summary, the feasibility and suitability of complex network theory are justified to identify critical nodes in power systems.

Critical links detection in stochastic networks: application to the transport networks

Purpose–The purpose of this paper is to study a multiple-origin-multiple-destination variant of dynamic critical nodes detection problem(DCNDP)and dynamic critical links detection problem(DCLDP)in stochastic networks.DCNDP and DCLDP consist of identifying the subset of nodes and links,respectively,whose deletion maximizes the stochastic shortest paths between all origins–destinations pairs,in the graph modeling the transport network.The identification of such nodes(or links)helps to better control the road traffic and predict the necessary measures to avoid congestion.Design/methodology/approach–A Markovian decision process is used to model the shortest path problem underdynamic trafficconditions.Effectivealgorithmstodeterminethe criticalnodes(links)whileconsideringthe dynamicity of the traffic network are provided.Also,sensitivity analysis toward capacity reduction for critical links is studied.Moreover,the complexity of the underlying algorithms is analyzed and the computational efficiency resulting from the decomposition operation of the network into communities is highlighted.Findings–The numerical results demonstrate that the use of dynamic shortest path(time dependency)as a metric has a significant impact on the identification of critical nodes/links and the experiments conducted on real world networks highlight the importance of sensitive links to dynamically detect critical links and elaborate smart transport plans.Research limitations/implications–The research in this paper also revealed several challenges,which call for future investigations.First,the authors have restricted our experimentation to a small network where the only focus is on the model behavior,in the absence of historical data.The authors intend to extend this study to very large network using real data.Second,the authors have considered only congestion to assess network’s criticality;future research on this topic may include other factors,mainly vulnerability.Practical implications–Taking into consideration the dynamic and stochastic nature in problem modeling enables to be effective tools for real-time control of transportation networks.This leads to design optimized smart transport plans particularly in disaster management,to improve the emergency evacuation effeciency.Originality/value–The paper provides a novel approach to solve critical nodes/links detection problems.In contrast to the majority of research works in the literature,the proposed model considers dynamicity and betweennesswhiletakingintoaccount the stochasticaspectof transportnetworks.Thisenables theapproach to guide the traffic and analyze transport networks mainly under disaster conditions in which networks become highly dynamic.