PoIR: A Node Selection Mechanism in Reputation-Based Blockchain Consensus Using Bidirectional LSTM Regression Model

This research presents a reputation-based blockchain consensus mechanism called Proof of Intelligent Reputation(PoIR)as an alternative to traditional Proof of Work(PoW).PoIR addresses the limitations of existing reputationbased consensus mechanisms by proposing a more decentralized and fair node selection process.The proposed PoIR consensus combines Bidirectional Long Short-Term Memory(BiLSTM)with the Network Entity Reputation Database(NERD)to generate reputation scores for network entities and select authoritative nodes.NERD records network entity profiles based on various sources,i.e.,Warden,Blacklists,DShield,AlienVault Open Threat Exchange(OTX),and MISP(Malware Information Sharing Platform).It summarizes these profile records into a reputation score value.The PoIR consensus mechanism utilizes these reputation scores to select authoritative nodes.The evaluation demonstrates that PoIR exhibits higher centralization resistance than PoS and PoW.Authoritative nodes were selected fairly during the 1000-block proposal round,ensuring a more decentralized blockchain ecosystem.In contrast,malicious nodes successfully monopolized 58%and 32%of transaction processes in PoS and PoW,respectively,but failed to do so in PoIR.The findings also indicate that PoIR offers efficient transaction times of 12 s,outperforms reputation-based consensus such as PoW,and is comparable to reputation-based consensus such as PoS.Furthermore,the model evaluation shows that BiLSTM outperforms other Recurrent Neural Network models,i.e.,BiGRU(Bidirectional Gated Recurrent Unit),UniLSTM(Unidirectional Long Short-Term Memory),and UniGRU(Unidirectional Gated Recurrent Unit)with 0.022 Root Mean Squared Error(RMSE).This study concludes that the PoIR consensus mechanism is more resistant to centralization than PoS and PoW.Integrating BiLSTM and NERD enhances the fairness and efficiency of blockchain applications.

Deducing Complete Selection Rule Set for Driver Nodes to Guarantee Network’s Structural Controllability

Structural controllability is critical for operating and controlling large-scale complex networks. In real applications, for a given network, it is always desirable to have more selections for driver nodes which make the network structurally controllable. Different from the works in complex network field where structural controllability is often used to explore the emergence properties of complex networks at a macro level,in this paper, we investigate it for control design purpose at the application level and focus on describing and obtaining the solution space for all selections of driver nodes to guarantee structural controllability. In accord with practical applications,we define the complete selection rule set as the solution space which is composed of a series of selection rules expressed by intuitive algebraic forms. It explicitly indicates which nodes must be controlled and how many nodes need to be controlled in a node set and thus is particularly helpful for freely selecting driver nodes. Based on two algebraic criteria of structural controllability, we separately develop an input-connectivity algorithm and a relevancy algorithm to deduce selection rules for driver nodes. In order to reduce the computational complexity,we propose a pretreatment algorithm to reduce the scale of network's structural matrix efficiently, and a rearrangement algorithm to partition the matrix into several smaller ones. A general procedure is proposed to get the complete selection rule set for driver nodes which guarantee network's structural controllability. Simulation tests with efficiency analysis of the proposed algorithms are given and the result of applying the proposed procedure to some real networks is also shown, and these all indicate the validity of the proposed procedure.

An mmWave Dual-Band Integrated Substrate Gap Waveguide Single Cavity Filter with Frequency Selectivity

A novel dual-band ISGW cavity filter with enhanced frequency selectivity is proposed in this paper by utilizing a multi-mode coupling topology.Its cavity is designed to control the number of modes,and then the ports are determined by analyzing the coupling relationship between these selected modes.By synthesizing the coupling matrix of the filter,a nonresonating node(NRN)structure is introduced to flexibly tune the frequency of modes,which gets a dualband and quad-band filtering response from a tri-band filter no the NRN.Furthermore,a frequency selective surface(FSS)has been newly designed as the upper surface of the cavity,which significantly improves the bad out-of-band suppression and frequency selectivity that often exists in most traditional cavity filter designs and measurements.The results show that its two center frequencies are f01=27.50 GHz and f02=32.92GHz,respectively.Compared with the dual-band filter that there is no the FSS metasurface,the out-of-band suppression level is improved from measured 5 dB to18 dB,and its finite transmission zero(FTZ)numbers is increased from measured 1 to 4 between the two designed bands.Compared with the tri-band and quadband filter,its passband bandwidth is expanded from measured 1.17%,1.14%,and 1.13% or 1.31%,1.50%,0.56%,and 0.57% to 1.71% and 1.87%.In addition,the filter has compact,small,and lightweight characteristics.

Management of lateral pelvic lymph nodes in rectal cancer:Is it time to reach an Agreement?

In this editorial,we proceed to comment on the article by Chua et al,addressing the management of metastatic lateral pelvic lymph nodes(mLLN)in stage II/III rectal cancer patients below the peritoneal reflection.The treatment of this nodal area sparks significant controversy due to the strategic differences followed by Eastern and Western physicians,albeit with a higher degree of convergence in recent years.The dissection of lateral pelvic lymph nodes without neoadjuvant therapy is a standard practice in Eastern countries.In contrast,in the West,preference leans towards opting for neoadjuvant therapy with chemoradiotherapy or radiotherapy,that would cover the treatment of this area without the need to add the dissection of these nodes to the total mesorectal excision.In the presence of high-risk nodal characteristics for mLLN related to radiological imaging and lack of response to neoadjuvant therapy,the risk of lateral local recurrence increases,suggesting the appropriate selection of strategies to reduce the risk of recurrence in each patient profile.Despite the heterogeneous and retrospective nature of studies addressing this area,an international consensus is necessary to approach this clinical scenario uniformly.

An Area Optimization Based Cooperative Localization Algorithm with Node Selection

In recent years,position information has become a key feature to drive location and context aware services in mobile communication.Researchers from all over the world have proposed many solu-tions for indoor positioning over the past several years.However,due to weak signals,multipath or non-line-of-sight signal propagation,accurately and efficiently localizing targets in harsh indoor environments re-mains a challenging problem.To improve the perfor-mance in harsh environment with insufficient anchors,cooperative localization has emerged.In this paper,a novel cooperative localization algorithm,named area optimization and node selection based sum-product al-gorithm over a wireless network(AN-SPAWN),is de-scribed and analyzed.To alleviate the high compu-tational complexity and build optimized cooperative cluster,a node selection method is designed for the cooperative localization algorithm.Numerical experi-ment results indicate that our proposed algorithm has a higher accuracy and is less impacted by NLOS errors than other conventional cooperative localization algo-rithms in the harsh indoor environments.

An efficient multi-relay selection scheme in cooperative communication system

Cooperative relaying has played an important role in rapid evolution of wireless communications.The cooperative performance strongly depends on the selected relays.In this paper,we concentrate on relay selection in amplify-and-forward(AF)cooperative communication system,and an optimal multi-relay selection scheme is put forward to minimize the average symbol error rate(SER)of the system.Firstly,for the minimum average SER,on the basis of the statistic channel information,we define a parameter named equivalent channel gain which describes the channel status of two phases in the cooperative process.Then,under the constraint of equal power allocation,an optimal relay selection scheme is proposed in ascending order of equivalent channel gain(ECG).The scheme implies that the suitable number of relay nodes should be selected under the different signal-to-noise ratio(SNR)ranges to minimize the average SER.Computer simulation results show that the average SER rate of the proposed scheme is lower than these of the other schemes.

The Next-Hop Node Selection Based GPSR in Vehicular Ad Hoc Networks

Vehicular Ad hoc Networks (VANETs) which is a special form of Mobile Ad hoc Networks (MANETs) has promising application prospects in the future. Due to the rapid changing of topology structure, how to find a route which can guarantee Quality of Service (QoS) is an important issue in VANETs. This paper presents an improved Greedy Perimeter Stateless Routing (GPSR) protocol based on our proposed next-hop node selection mechanism. Firstly, we define the link reliability in two cases which take the movement direction angle between two vehicles into consideration. Then we propose a next-hop node selection mechanism based on a weighted function which consists of link reliability between the sender node and next-hop candidate node, distance between next-hop candidate node and the destination, movement direction angle of next-hop candidate node. At last, an improved GPSR protocol is proposed based on the next-hop node selection mechanism. Simulation results are presented to evaluate the performance of the improved GPSR protocol, which shows that the performance including packet delivery ratio and average end-to-end delay of the proposed protocol is better in some situations.

外周血E-selectin、P-selection及K-ras基因突变水平在胰腺癌中的表达及意义

目的探讨外周血内皮细胞选择素(E-selectin)、血小板选择素(P-selection)及K-ras基因突变水平在胰腺癌中的表达及意义。方法选择2019年2月—2020年2月收治的胰腺癌60例作为胰腺癌组,选择同期健康体检的健康人60例作为对照组。应用双抗夹心法酶联免疫吸附试验(ELISA)检测2组外周血E-selectin及P-selection水平,使用肽核酸钳制实时定量PCR法检测外周血中K-ras基因突变情况。分析2组外周血E-selectin、P-selection水平及其与胰腺癌临床病理特征的关系。检测外周血K-ras基因突变率及与临床病理特征的关系。结果胰腺癌组外周血E-selectin水平高于对照组,P-selection水平低于对照组(P<0.01)。外周血E-selectin、P-selection水平与肿瘤分期、淋巴结转移、肝转移有关(P<0.01),与肿瘤部位无关(P>0.05)。外周血K-ras基因突变率为48.3%。胰腺癌患者外周血K-ras基因突变与性别相关(P<0.01),而与患者年龄、分期、淋巴结及肝转移和肿瘤部位无关(P>0.05)。结论外周血E-selectin和P-selection异常表达与外周血K-ras基因检测同胰腺癌发生发展及预后密切相关,对胰腺癌早期筛查、诊断、指导临床治疗起到重要作用。

Detection of Insider Selective Forwarding Attack Based on Monitor Node and Trust Mechanism in WSN

The security problems of wireless sensor networks (WSN) have attracted people’s wide attention. In this paper, after we have summarized the existing security problems and solutions in WSN, we find that the insider attack to WSN is hard to solve. Insider attack is different from outsider attack, because it can’t be solved by the traditional encryption and message authentication. Therefore, a reliable secure routing protocol should be proposed in order to defense the insider attack. In this paper, we focus on insider selective forwarding attack. The existing detection mechanisms, such as watchdog, multipath retreat, neighbor-based monitoring and so on, have both advantages and disadvantages. According to their characteristics, we proposed a secure routing protocol based on monitor node and trust mechanism. The reputation value is made up with packet forwarding rate and node’s residual energy. So this detection and routing mechanism is universal because it can take account of both the safety and lifetime of network. Finally, we use OPNET simulation to verify the performance of our algorithm.

Impact of antenna and beam-selection-based sectored relay planning for 備 performance evaluation of 4G LTE-A tri-sectored cell

The deployment of Relay Nodes (RNs) in 4G LTE-A networks, mainly originating from the wireless backhaul link, provides an excellent network planning tool to enhance system performance. Better coordination between the base station and relays to mitigate inter-cell interference becomes an important aspect of achieving the required system performance, not only in the single-cell scenario, but also in multi-cell scenarios. In this paper, we model and analyze two basic approaches for designing a 4G LTE-A tri-sectored cellular system. The approaches are based on Antenna Selection Sectored Relaying (ASSR) and Beam Selection Sectored Relaying (BSSR). The main purpose of the proposed schemes is to enhance system performance by improving the quality of the wireless relay backhaul link. In this technique, antenna selection takes into consideration Non-Line-Of-Sight (NLOS) communication, whereas BSSR considers the case of Line-Of-Sight (LOS) communication using heuristic beam forming approach. The resource allocation problem has also been investigated for relay based cooperative LTE-A trisectored cell in the downlink. The best possible location for relay node in the sector, power allocation and MIMO channel modeling is formulated as an optimization problem with the aim of maximizing the end to end link rate and the Signal to Interference plus Noise Ratio (SINR) of 4G LTE-A systems. Power allocation/optimization has been solved by means of the duality equation of the stationary Karush-Kuhn-Tucker (KKT) cond让ion and is used to derive optimal values for the beam forming vector on both the relay as well as the access link. The performance of the proposed scheme is verified through simulations carried out using MATLAB software. The simulation results show a significant improvement in the SINR, throughput capacity, and coverage area of the 4G LTE-A cell, while guaranteeing better quality of service.

无线传感网络拥塞控制中节点选择强制博弈方法

无线传感网络中节点数据流量较大,分布范围较广,节点选择寻优计算复杂,导致浪费大量算力在节点选择上,拥塞控制效果不佳。提出一种无线传感网络拥塞控制中节点选择强制博弈方法,计算单条网络链路传输成本,依据传输数据耗费能量,计算传输节点可用能量比值,在传输变量权重值基础上,求得传输节点实际拥堵指数,完成节点选择。计算网络连接层的数据包丢弃概率,确定网络拥塞程度,汇聚节点数据流建立节点选择强制博弈模型,明确传感网络稳态传输条件,利用流量正态分布算法,在节点选择博弈中做出强制选择。经仿真分析证明:所提方法分组递交率保持在83%以上,丢包数量保持在100 pkt/s之内,网络传输节点端到端的延迟在0.3 s以内。

无需先验测量误差的定位节点选择方法

针对现有定位节点选择算法依赖先验测量误差的问题,研究了一种不依赖先验测量误差的时差与频差无源定位节点选择方法,该方法将两步加权最小二乘定位算法中目标估计误差协方差作为目标函数。在给定可用定位节点数目的情况下,通过引入一组布尔量构建关于目标函数为带约束的最小估计误差寻优问题,通过半定松弛技术将非凸问题转为半定规划问题进行求解,依据最小化问题特性,使得所提算法不依赖先验测量误差。仿真结果表明,不依赖测量误差的方法与穷举搜索法相比在定位性能上无太大差别;相比于穷尽搜索算法,所提方法复杂度低、实时性好。同时,仿真结果进一步表明在对运动目标定位过程中,及时调整定位节点组合的必要性。

图神经网络节点分类任务基准测试及分析

图神经网络(Graph Neural Network,GNN)模型由于采用端到端的模型架构,在训练过程中能够更好地将节点隐藏特征的学习和分类目标协同起来,相比图嵌入(Graph Embedding)的方法,其在节点分类等任务上得到了较大的性能提升。但是,已有图神经网络模型实验对比阶段普遍存在的数据集类型单一、样本量不足、数据集切分不规范、对比模型规模及范围有限、评价指标单一、缺乏模型训练耗时对比等问题。为此,文中选取了包括cora,citeseer,pubmed,deezer等在内的来自不同领域(引文网络、社交网络及协作网络等)的共计20种数据集,以准确率、精确率、召回率、F-score值及模型训练耗时为多维评价指标,在FastGCN,PPNP,ChebyNet,DAGNN等17种主流图神经网络模型上,进行了全面且公平的节点分类任务基准测评,进而为真实业务场景下的模型选择提供了决策参考。通过基准测试实验发现,一方面,影响模型训练速度的因素排名依次是节点属性维度、图节点规模及图边的规模;另一方面,并不存在赢者通吃的模型,即不存在在所有数据集下全都表现优异的模型,特别是在公平的基准测试配置环境下,结构简洁的模型反而比复杂的GNN模型有着更好的性能表现。

自由节点差分法寻点策略研究及验证

混合网格具有良好的贴体性,适用于Navier-Stokes方程的计算,但在网格交界面处需要通过插值进行流场信息交换,而这一过程会引入误差。陈洁等提出了一种适用于无序网格点的自由节点差分计算方法,该方法可对重叠网格交界面流场进行差分计算,无须采用插值方法进行流场信息传递,解决了插值方法引入误差的问题。但该自由节点差分法的计算模板需要从中心点周围的点云中选择网格点构成,不同选点策略对计算结果的影响不同。针对自由节点差分法的选点需求,本文综合考虑角度、正交性、距离等因素,提出了几种不同选点策略,并利用数值实验进行了验证。结果表明,本文提出的选点策略符合自由节点差分法的构造思想,均能获得稳定的收敛解,其中模板点与中心点距离对计算精度影响最大,是选点策略的首要影响因素。

基于网络结构设计的图神经网络特征选择方法

近年来,研究人员针对图神经网络(GNN)提出了许多改进的模型架构设计,推动了各种预测任务的性能提升。但大多数GNN变体在开始都认为节点的特征同等重要,而实际情况并非如此。针对这个问题,提出一种特征选择方法来改进现有模型,并为数据集选择出重要特征子集。所提方法由特征选择层和标签-特征单独映射两个组件构成。在特征选择层中使用Softmax归一化器和特征“软选择器”进行特征选择,在标签-特征单独映射思想下设计模型结构,为不同的标签选择对应的相关特征子集,并将多个相关特征子集作集合并运算得到最终数据集的重要特征子集。选取图注意力网络(GAT)和GATv2模型为基准模型,将算法应用到基准模型中得到新模型。实验结果表明,所提模型在6个数据集上执行节点分类任务时,准确率相较于基准模型提升了0.83%~8.79%;新模型也为6个数据集选择了对应的重要特征子集,这些重要特征子集的特征数量占各自数据集总特征数的3.94%~12.86%,将重要特征子集作为基准模型的新输入后仍然获得了95%以上的准确率(使用了所有特征),即在保证准确率的基础上减小了模型的规模。可见,所提方法能够提高节点分类准确率,并有效地为数据集选择对应的重要特征子集。

异构大规模分布式网络设计与性能评估

提出了一种面向6G的异构大规模分布式网络(Het-LDN)。该网络由大量异构的分布式无线节点构成,具有低成本、低功耗、高性能、易部署和易扩展等特征,满足未来无线通信的各项需求,包括实现极致的蜂窝系统容量,保证超高可行性传输,支持海量用户同时接入和取得一致性的用户体验。介绍了分层的分布式网络结构与多链路协同传输方案,并通过仿真实验展示了用户吞吐量的性能优势。认为该网络可成为面向6G的具备强竞争力的商业化解决方案。

基于超网络理论的高铁快运枢纽节点选址与分级研究

随着我国高速铁路的发展,大幅度实现了客货分流的既有目标,运力充足促进了高铁快运的发展,然而我国尚未形成以枢纽节点为中心的高铁快运网络,货物的集疏运效率较低,作业系统尚未完善,因而对枢纽节点的选择和分级是提高高铁快运效率的重要手段。首先分析我国高铁快运的发展现状,结合超网络理论对高铁快运枢纽城市进行选择与分级,计算节点静态拓扑参数得到枢纽节点初选集,再从节点失效后对网络韧性的影响角度出发对初选集中节点进行筛选,计算网络鲁棒性来衡量线网韧性从而证明结论合理性,确定节点位置集合;使用Logit模型标定高速铁路货运占比,计算节点加权介数,最后利用LSTM网络对货运量进行预测,确定我国高铁快运一级枢纽节点集合,按服务区域统筹货物集疏运工作,提高高铁快运的市场竞争力。

基于声誉的分布式联邦学习节点选择算法

由于隐私泄露的风险越来越大,而采集的数据中通常包含大量隐私信息,使数据的采集者不愿意共享自己的数据,造成“数据孤岛”,联邦学习能够实现数据不离本地的数据共享,但其在多机构数据共享中还存在一些问题,一方面中央服务器集中处理信息造成昂贵的成本,易产生单点故障,另一方面,对于多机构数据共享而言,参与节点中混入恶意节点可能影响训练过程,导致数据隐私泄露,基于上述分析,文章提出了一种将区块链和联邦学习相结合的以实现高效节点选择和通信的新的分布式联邦学习架构,解放中央服务器,实现参与节点直接通信,并在此架构上提出了一种基于信誉的节点选择算法方案(RBLNS),对参与节点进行筛选,保证参与节点的隐私安全;仿真结果表明,RBLNS能够显着提高模型的实验性能。

能耗均衡与节能的自适应水下路由协议

针对水下传感器网络中节点能耗不均衡和能量有限的问题,提出一种能耗均衡与节能的自适应水下路由协议ECBES(energy consumption balanced and energy saving adaptive underwater routing protocol)。构建双区非均匀分层拓扑。基于能耗均衡因子,利用拓扑和节点剩余能量计算节点转发优先级,实现自适应转发节点选择,均衡网络能耗。与此同时,通过候选转发区域各分区域中节点参与转发数据包的比例确定次优候选转发区域,将次优候选转发区域作为初始策略,利用策略迭代思想确定最优候选转发区域,保证投递率的同时减少不同网络规模中重复数据包的转发,降低网络的整体能耗。仿真结果表明,ECBES相比VBF、ES-VBF和ALRP,在不同节点数量下,节点死亡率均最低,在保证数据包投递率的同时,能耗最少。