Undoubtedly,uncooperative or malicious nodes threaten the safety of Internet of Vehicles(IoV)by destroying routing or data.To this end,some researchers have designed some node detection mechanisms and trust calculatin...Undoubtedly,uncooperative or malicious nodes threaten the safety of Internet of Vehicles(IoV)by destroying routing or data.To this end,some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication,data,energy,etc.,to detect and evaluate vehicle nodes.However,it is difficult to effectively assess the trust level of a vehicle node only by message forwarding,data consistency,and energy sufficiency.In order to resolve these problems,a novel mechanism and a new trust calculating model is proposed in this paper.First,the four tuple method is adopted,to qualitatively describing various types of nodes of IoV;Second,analyzing the behavioral features and correlation of various nodes based on route forwarding rate,data forwarding rate and physical location;third,designing double layer detection feature parameters with the ability to detect uncooperative nodes and malicious nodes;fourth,establishing a node correlative detection model with a double layer structure by combining the network layer and the perception layer.Accordingly,we conducted simulation experiments to verify the accuracy and time of this detection method under different speed-rate topological conditions of IoV.The results show that comparing with methods which only considers energy or communication parameters,the method proposed in this paper has obvious advantages in the detection of uncooperative and malicious nodes of IoV;especially,with the double detection feature parameters and node correlative detection model combined,detection accuracy is effectively improved,and the calculation time of node detection is largely reduced.展开更多
For fault characteristics of cyber-physical-systems(CPS)based distribution network,a spatiotemporal incidence matrix to represent correlation of concurrent faults on cyberspace and physical space is proposed,and strat...For fault characteristics of cyber-physical-systems(CPS)based distribution network,a spatiotemporal incidence matrix to represent correlation of concurrent faults on cyberspace and physical space is proposed,and strategies of fault location,removal,and recovery of concurrent faults are analyzed in this paper.Considering the multiple objectives of minimum network loss,voltage deviation,and switching operation times,a collaborative power supply restoration model of a CPS-based distribution network with the strategy that restoration of the communication layer is prior to the physical layer is constructed using the Dijkstra’s dynamic routing algorithm and second-order cone relaxation distribution network reconfiguration method,to realize orderly recovery of a distribution network during CPS concurrent faults.Related investigations are made based on the DCPS-160 case,and the accuracy and effectiveness of the proposed model are also verified.展开更多
基金This research is supported by the National Natural Science Foundations of China under Grants Nos.61862040,61762060 and 61762059The authors gratefully acknowledge the anonymous reviewers for their helpful comments and suggestions.
文摘Undoubtedly,uncooperative or malicious nodes threaten the safety of Internet of Vehicles(IoV)by destroying routing or data.To this end,some researchers have designed some node detection mechanisms and trust calculating algorithms based on some different feature parameters of IoV such as communication,data,energy,etc.,to detect and evaluate vehicle nodes.However,it is difficult to effectively assess the trust level of a vehicle node only by message forwarding,data consistency,and energy sufficiency.In order to resolve these problems,a novel mechanism and a new trust calculating model is proposed in this paper.First,the four tuple method is adopted,to qualitatively describing various types of nodes of IoV;Second,analyzing the behavioral features and correlation of various nodes based on route forwarding rate,data forwarding rate and physical location;third,designing double layer detection feature parameters with the ability to detect uncooperative nodes and malicious nodes;fourth,establishing a node correlative detection model with a double layer structure by combining the network layer and the perception layer.Accordingly,we conducted simulation experiments to verify the accuracy and time of this detection method under different speed-rate topological conditions of IoV.The results show that comparing with methods which only considers energy or communication parameters,the method proposed in this paper has obvious advantages in the detection of uncooperative and malicious nodes of IoV;especially,with the double detection feature parameters and node correlative detection model combined,detection accuracy is effectively improved,and the calculation time of node detection is largely reduced.
基金This work is supported by Funds for International Cooperation and Exchange of the National Natural Science Foundation of China(Grant No.52061635104,Sustainable urban power supply through intelligent control and enhanced restoration of AC/DC networks).
文摘For fault characteristics of cyber-physical-systems(CPS)based distribution network,a spatiotemporal incidence matrix to represent correlation of concurrent faults on cyberspace and physical space is proposed,and strategies of fault location,removal,and recovery of concurrent faults are analyzed in this paper.Considering the multiple objectives of minimum network loss,voltage deviation,and switching operation times,a collaborative power supply restoration model of a CPS-based distribution network with the strategy that restoration of the communication layer is prior to the physical layer is constructed using the Dijkstra’s dynamic routing algorithm and second-order cone relaxation distribution network reconfiguration method,to realize orderly recovery of a distribution network during CPS concurrent faults.Related investigations are made based on the DCPS-160 case,and the accuracy and effectiveness of the proposed model are also verified.
