Analysis of identification methods of key nodes in transportation network

The identification of key nodes plays an important role in improving the robustness of the transportation network.For different types of transportation networks,the effect of the same identification method may be different.It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks.Based on the knowledge of complex networks,the metro networks and the bus networks are selected as the objects,and the key nodes are identified by the node degree identification method,the neighbor node degree identification method,the weighted k-shell degree neighborhood identification method(KSD),the degree k-shell identification method(DKS),and the degree k-shell neighborhood identification method(DKSN).Take the network efficiency and the largest connected subgraph as the effective indicators.The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

ANCAEE: A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks

One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.

Energy-Efficient Mobile Data Collection Adopting Node Cooperation in an Underwater Acoustic Sensor Network

This paper considers an underwater acoustic sensor network with one mobile surface node to collect data from multiple underwater nodes,where the mobile destination requests retransmission from each underwater node individually employing traditional automatic-repeat-request(ARQ) protocol.We propose a practical node cooperation(NC) protocol to enhance the collection efficiency,utilizing the fact that underwater nodes can overhear the transmission of others.To reduce the source level of underwater nodes,the underwater data collection area is divided into several sub-zones,and in each sub-zone,the mobile surface node adopting the NC protocol could switch adaptively between selective relay cooperation(SRC) and dynamic network coded cooperation(DNC) .The difference of SRC and DNC lies in whether or not the selected relay node combines the local data and the data overheard from undecoded node(s) to form network coded packets in the retransmission phase.The NC protocol could also be applied across the sub-zones due to the wiretap property.In addition,we investigate the effects of different mobile collection paths,collection area division and cooperative zone design for energy saving.The numerical results showthat the proposed NC protocol can effectively save energy compared with the traditional ARQ scheme.

Coordinated node scheduling for energy-conserving in large wireless sensor networks

Aiming at developing a node scheduling protocol for sensor networks with fewer active nodes,we propose a coordinated node scheduling protocol based on the presentation of a solution and its optimization to determine whether a node is redundant.The proposed protocol can reduce the number of working nodes by turning off as many redundant nodes as possible without degrading the coverage and connectivity.The simulation result shows that our protocol outperforms the peer with respect to the working node number and dynamic coverage percentage.

Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks

In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks.This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless networks.The proposed IM-EECNL technique involves two major processes namely node localization and clustering.Firstly,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the nodes.Secondly,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the network.Besides,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and load.The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985.

Employing Orphan Nodes to Avoid Energy Holes in Wireless Sensor Networks

When energy consumption by wireless sensor nodes gets off balance, partitions in the network appear because several of the nodes stop functioning. The respective network’s lifetime also diminishes. This problem is commonly known as the “hot spot” or “energy hole” phenomenon. To resolve this issue, a Multi-Hop Decentralized Cluster-Based Routing (MDCR) protocol is proposed. This algorithm uses orphan nodes as intermediate nodes to form inter-cluster multi-hop routing and balance the energy consumption among sensor nodes. Simulation experiments have shown that MDCR is significantly better at prolonging network lifetime compared to the Adaptive Decentralized Re-Clustering Protocol.

Steadfast Energy Proficient Sensor Node Activation System in Wireless Networks Lifetime Enhancement

The wireless sensor network (WSN) is one of the budding exploring areas and fast rising fields in wireless communications. The sensor nodes in the network are generally small-size, low-cost, low-power and multi-function capabilities. Wireless sensor networks (WSNs) are used for various applications;since numerous sensor nodes are usually deployed on remote and inaccessible places, the employment and preservation should be easy and scalable. Sensor nodes in the field being run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the long life of the network. This paper work proposes a hierarchical based node activation routing technique which shows energy efficiency. This technique selects cluster head with highest residual energy in each communication round of transmission to the base station from the cluster heads. Hierarchical based node activation routing technique with different levels of hierarchy simulation results prolongs the lifetime of the network compared to other clustering schemes and communication rounds of simulation increase significantly.

A Chain Routing Algorithm Based on Traffic Prediction in Wireless Sensor Networks

As a representative of chain-based protocol in Wireless Sensor Networks (WSNs), EEPB is an elegant solution on energy efficiency. However, in the latter part of the operation of the network, there is still a big problem: reserving energy of the node frequently presents the incapacity of directly communicating with the base station, at the same time capacity of data acquisition and transmission as normal nodes. If these nodes were selected as LEADER nodes, that will accelerate the death process and unevenness of energy consumption distribution among nodes.This paper proposed a chain routing algorithm based ontraffic prediction model (CRTP).The novel algorithmdesigns a threshold judgment method through introducing the traffic prediction model in the process of election of LEADER node. The process can be dynamically adjusted according to the flow forecasting. Therefore, this algorithm lets the energy consumption tend-ing to keep at same level. Simulation results show that CRTP has superior performance over EEPB in terms of balanced network energy consumption and the prolonged network life.

Research on Accurate Information Pushing Based on Human Network

Based on the social network analysis methods and human network, this paper randomly selected 44 students (31 males and 13 females) as the research objects, and it used the UCINET software to analyze the friendship between them of which 43 used WeChat and 44 used QQ, and it also used the tool Netdraw to visualize the network sociogram. By mining the four aspects of density, accessibility, centrality, block model, the results demonstrated that QQ social network and WeChat social network existed the phenomenon of small world, leaders and subgroups, and the key nodes of QQ human network were more than WeChat network. Through using the key nodes, it can push the precise and efficient information and improve the accuracy of information transmission and impact among network members.

A Reliable and Secure Smart Grid Communication Network Using a Comprehensive Cost Function

SG （smart grids） is an intelligent power grid in which the diverse nodes should communicate different types of information which have different communication requirements with CS （control stations）. There exist several RATs （radio access technologies）, with diversification in quality of service character which respect to the SG nodes communication requirements. On the other side, spectrum is becoming a rare source and its demands request is increasing exponentially. Therefore, resource allocation to support different types of SG nodes should be elaborated so that the resource efficiency is maximized while the SG communication requirements are respected. Using a CF （cost function） based on the SG node requirements and RATs characteristics to find the desirability value of every RATs for a certain node type accomplish this goal in combination with prioritizing the different SG nodes types based on SG goals by creating a priority table for RATs and different SG node types. The main node communication requirements are formulized to be used in the CF in this paper. The numerical results show that the proposed method defines the desirability value of each RAT for a certain SG node type that helps to make a priority table by using the SG node prioritization table.

Aviation armament system-of-systems modeling and identification method of vulnerable nodes based on interdependent network

Aiming at the problem that it is difficult to build model and identify the vulnerable equipment for aviation armament System-of-Systems(SoS)due to complex equipment interaction relationships and high confrontation,the interdependent network theory is introduced to solve it.Firstly,a two-layer heterogeneous interdependent network model for aviation armament SoS is proposed,which reflects the information interaction,functional dependency and inter-network dependence effectively.Secondly,using the attack cost to describe the confrontation process and taking the comprehensive impact on kill chains as the entry point,the node importance index and the attack cost measurement method are constructed.Thirdly,the identification of vulnerable nodes is transformed into the optimization problem of node combinatorial selection,and the vulnerable node identification method based on tabu search is proposed.Based on vulnerable nodes,a robustness enhancement strategy for aviation armament SoS network is presented.Finally,the above methods are used to an aerial confrontation SoS,and the results verify the rationality and effectiveness of the proposed methods.

Adversarial attacks against dynamic graph neural networks via node injection

Dynamic graph neural networks(DGNNs)have demonstrated their extraordinary value in many practical applications.Nevertheless,the vulnerability of DNNs is a serious hidden danger as a small disturbance added to the model can markedly reduce its performance.At the same time,current adversarial attack schemes are implemented on static graphs,and the variability of attack models prevents these schemes from transferring to dynamic graphs.In this paper,we use the diffused attack of node injection to attack the DGNNs,and first propose the node injection attack based on structural fragility against DGNNs,named Structural Fragility-based Dynamic Graph Node Injection Attack(SFIA).SFIA firstly determines the target time based on the period weight.Then,it introduces a structural fragile edge selection strategy to establish the target nodes set and link them with the malicious node using serial inject.Finally,an optimization function is designed to generate adversarial features for malicious nodes.Experiments on datasets from four different fields show that SFIA is significantly superior to many comparative approaches.When the graph is injected with 1%of the original total number of nodes through SFIA,the link prediction Recall and MRR of the target DGNN link decrease by 17.4%and 14.3%respectively,and the accuracy of node classification decreases by 8.7%.

基于物联网农业灌溉系统精准控制模型的研究

为进一步提升我国农业灌溉系统的综合作业效率,体现灌溉的先进性与科学性,提出以精准控制模型为切入点,以物联网技术为主体支撑平台,针对其作业系统展开设计与优化。通过引入物联网强大的系统性架构,规范与强化各网络节点的部署与协作关系,科学搭建用于实现精准灌溉控制的数学模型,同时导入合理的系统软件设计程序与硬件功能组件配置,形成完整集成式的农业智能灌溉系统。结果表明:基于物联网平台技术的精准控制模型应用后,整体的作业效率得到显著提升,系统精准度、系统响应率分别相对提高了6.25%和7.68%,动作延迟率相对降低了2.72%,灌溉节水效率提升至91.50%。物联网平台下的精准控制模型应用效果良好,设计理念正确,可为灌溉领域实施节能降耗提供参考。

气象灾害下的油气站场设备脆弱节点辨识方法

油气站场是保障我国石油与天然气等能源运输、储存体系的重要组成部分,油气站场的安全稳定运行是油气系统,乃至国家经济发展的重要一环。我国面积较大,包含多种气候地区,不同地域易发暴雨、雷电、台风等气象灾害。气象灾害发生在油气站场及其附近时可能会对相关设施造成破坏,导致站场处于异常工况中运行,甚至引发事故。常见的石油及相关液态加工产品的储运站场,介质除本身具有易燃易爆特性外,一般还具有一定的挥发性,易形成可燃气体云团。天然气站场常伴随高压运行条件,站场一旦出现异常工况或事故会使厂区内部工作人员的生命安全及周边环境都承受较大风险。气象灾害往往难以避免,但可以通过有针对性地增加安全措施加强站场在气象灾害条件下的稳定性,降低气象灾害带来的风险。为了达到上述目的,综合考虑油气站场的设备在遇到暴雨、雷暴等气象灾害时,更容易发生油气泄漏、爆炸等事故的情况,本文根据气象灾害发生场景,及相关场景下可能发生的灾害演化路径提出了一种定量的脆弱节点辨识方法。面对不同的环境风险,现有方法对于站场设备脆弱节点辨识缺乏精细度与准确度,错误辨识脆弱节节点不仅会导致防护过程中人力物力的浪费,更可能导致储罐管道的泄漏,甚至引发爆炸。本文对重力模型进行改进,结合鲁汶算法,提出基于社团分析模型的设备脆弱节点辨识方法。通过实验分析,得到暴雨天气、雷暴天气下的脆弱节点,并利用提出模型对历史案例进行分析,得到结果与实际调查情况较为吻合。相较于其他分析方法,社团分析模型精细度提高了10%以上,分析结果准确率提高了10%以上,召回率提高了14%以上。实验结果表明,本文所提方法可以实现多种极端天气下的脆弱节点辨识,且能对节点进行更精准的定位。

基于超网络的军事交通运输网络节点价值评估方法

针对军事交通运输网络中的高价值目标选择问题,提出一种基于超网络的节点价值评估方法。考虑多层网络内部和网络之间的交互机制,构建由通行枢纽子网、军事力量子网和后勤保障子网组成的军事交通运输超网络模型;提出综合拓扑维度和功能维度的超网络综合效能评价算法,在此基础上运用节点删除法,获得超网络中节点的体系价值和优先打击顺序。实验结果表明:节点的功能属性对其体系价值起决定性作用,且所处位置越优、邻近节点越重要,其体系价值越高;经过多轮打击后,通过该方法获得的节点打击排序相近,表明了该方法的鲁棒性;与现有方法相比,该方法能够全面客观地判断目标的重要度,有效提高决策的准确率,具有较高的战场普适性。

航路网络关键脆弱节点分析方法

为了提高航班准点率,保障运行安全,缓解空管部门的压力,识别出航路网络的脆弱环节及关键脆弱节点并对此进行改善,能够有效地保障航班正常运行,进一步提高民航服务水平。基于广州-珠海空域的航路网络数据,构建空中交通网络并选取三个复杂网络脆弱性统计特征,进行攻击实验,开展关键脆弱节点分析,结果表明,在广州-珠海空域网络中,脆弱性较高的节点主要有从化航路点和石龙航路点,平洲航路点的脆弱性也相对较高,这些节点的失效将会使该区域的脆弱性显著提升;而高要航路点、ATAGA航路点、龙门航路点三点脆弱性较低,这些航路点的失效并不会对整个网络的脆弱性造成太大影响。

计及设备健康指数的配电网节点脆弱性评估

节点脆弱性评估对配电网风险预警、安全运行具有关键作用。为此,提出了一种计及设备健康指数的配电网节点脆弱性评估方法。首先,从设备维度出发,基于全生命周期理论得到节点设备本身和网络中的健康指数,以此得到配电网节点脆弱性预评估方案;然后,针对配电网的辐射状特性,在系统维度下基于复杂网络理论和风险理论,提出了改进评估指标;接着,利用改进评估指标对设备维度下配电网节点脆弱性预评估方案进行再辨识,得到配电网节点脆弱性排序;最后,以IEEE 33节点配电系统为例,对算例结果进行分析,并与其他文献结果进行对比,验证了所提方法的合理性和可行性。

自建房火灾致因网络拓扑特征及脆弱性研究

为预防我国自建房火灾的发生,首先,基于事故致因“2-4”模型分析39起自建房火灾事故案例,编码得到48个致因因素和128条致因关系;然后,基于复杂网络理论构建自建房火灾致因网络拓扑结构模型,分析网络的度、介数和接近中心性等拓扑特征;最后,以最大强连通子图相对大小、最大弱连通子图相对大小和全局网络效率作为网络脆弱性评价指标,仿真分析不同节点攻击策略下网络的脆弱性,得到自建房火灾关键致因因素,并提出防灾措施及建议。结果表明:自建房火灾致因网络具有小世界效应和无标度特性,致因间转换路径较短,少数关键节点与大多数节点相连;自建房火灾致因网络在遭受单个节点故障和随机累积节点故障时具有一定的鲁棒性,遭受蓄意累积节点攻击时,表现出较强的脆弱性;采用累积节点攻击策略中的蓄意度攻击时,网络表现出的脆弱性最强,度排序靠前的节点较为重要,是自建房火灾关键致因因素,为自建房消防安全管理提供理论参考。

高速铁路复杂网络特性与脆弱性研究

为研究我国高速铁路的网络特性和脆弱性,利用复杂网络理论构建高铁网络模型并分析其特性,在此基础上,通过Pajek软件计算并分析节点度、平均路径长度、聚集系数、中介中心性等网络特性指标,利用改进后的节点重要度公式对重要节点城市进行挖掘,再对高铁网络进行随机攻击和蓄意攻击,通过网络效率与最大连通子图相对大小分析网络的脆弱性,结果表明:高铁网络具有小世界网络特性,随机攻击下网络表现出较好的连通性,蓄意攻击下呈现脆弱性。优先加强重要节点城市的连通性,提升高铁网络的抗毁性,可以更好地保障高速铁路运营的稳定性和可靠性,进一步促进区域经济和社会的发展。