基于虚拟传热的能耗均衡幂律重部署算法

针对大规模双层无线传感器网络自移动传感器节点覆盖控制的能耗均衡问题,提出一种基于虚拟传热的重部署算法。建立了以二次熵为基础的幂律熵模型,设计传感器节点与汇聚节点之间的绝对移动方法;利用邻居节点之间幂律熵流动的平衡关系,建立熵平衡方程,采用相对熵求得相对移动中参照节点选取概率的权重,设计相对移动方法。叠加两种自移动方法,进行迭代,达到网络熵平衡。实验表明,所提算法能够高效实现能耗均衡,及时避免能量空洞,延长了网络生命周期,并提升了覆盖率。     

New mixed broadcast scheduling approach using neural networks and graph coloring in wireless sensor network

Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem (BSP) is aimed to schedule each node in different slot of fixed length frame at least once, and the objective of BSP is to seek for the optimal feasible solution, which has the shortest length of frame slots, as well as the maximum node transmission. A two-stage mixed algorithm based on a fuzzy Hopfield neural network is proposed to solve this BSP in wireless sensor network. In the first stage, a modified sequential vertex coloring algorithm is adopted to obtain a minimal TDMA frame length. In the second stage, the fuzzy Hopfield network is utilized to maximize the channel utilization ratio. Experimental results, obtained from the running on three benchmark graphs, show that the algorithm can achieve better performance with shorter frame length and higher channel utilizing ratio than other exiting BSP solutions.     

基于UKF的自组织模糊神经网络训练算法

如何生成最优的模糊规则数及模糊规则的自动生成和修剪是模糊神经网络训练算法研究的重点,针对这一问题,提出了基于无迹卡尔曼滤波（unscented Kalman filter, UKF）的自组织模糊神经网络的训练算法。分析了模糊神经网络的非线性动力系统表示,并用递推最小二乘法（recursive least square, RLS）和UKF分别学习线性和非线性的参数,给出了模糊规则生成的准则和参数更新的策略;然后,用误差下降率方法作为模糊规则修剪的策略,删除作用不大的规则。通过典型的函数逼近和系统辨识实例,表明所提算法得到的模糊神经网络的结构更为紧凑,泛化性能更佳。     

Command and control model based on complex information relation integration北大核心CSCD

In order to describe collaborative decision-making process, the command and control model is put forward based on complex information relation integrtion and OODA. The characteristics of individual decision-making are analyzed, the complex information relation is considered as the cause of OODA difficulty to describe collaborative decision-making exactly. From the perspective of armament system of systems combat, the information, data, intelligence and knowledge is defined based on knowledge management and Shannon's entropy theory. The basic element is confirmed and the information flow way is analyzed which in the physical, information, cognitive and social domains. From the perspective of information, the armament system of systems complex networks model framework is put forward based on the idea of using OODA to guide armament system of systems complex networks model design. The data, information, intelligence and knowledge flow is analyzed and the describing meta-model is put forward. Using the reticular structure of OODA to describe collaborative decision-making idea is proposed, the command and control model is put forward based on the idea, the simulating tool ExtendSim is used for simulation analysis and results show that our work offer a reference for innovate command and control thory. ©, 2015, The Journal Agency of Complex Systems and Complexity Science. All right reserved.     

Codebook selected beamforming algorithm for multiuser MIMO systems

For reducing the inter-user interference in multi-user multiple-input multiple-output(MU-MIMO) wireless communication systems,e.g.,MIMO-orthogonal frequency division multiplexing(MIMO-OFDM) systems,it is often desirable to the complex preprocessing at the transmitter.This paper proposes a multi-user beamforming algorithm with sub-codebook selection.Based on the minimal leakage criterion,the codebook selection,limited feed-forward and minimum mean square error(MMSE) detection are combined in the proposed algorithm.This avoids the complex channel matrix decomposition and inversion.Consequently,the computational complexity at the transmitter is significantly reduced.Simulation results show that the proposed algorithm performs better than existing beamforming algorithms.     

基于组合权重的异构无线网络选择算法

针对异构网络环境下网络选择算法采用单一方法确定判决指标权重存在的片面性问题,提出了基于组合权重的异构无线网络选择算法.首先根据用户需求建立判决矩阵,并进行层次分析,得到各判决指标的主观权重,同时对判决指标进行熵值处理,得到其客观权重;然后对主客观权重进行博弈均衡,确定指标的组合权重;最后对备选网络进行灰色关联分析,并运用组合权重对关联系数进行加权排序,得到最优接入网络.仿真实验证明:该方法能综合考虑多种接入判决指标,提高了异构网络中多模终端选择网络的准确性.     

The Dynamics of Two-State Public Opinion Propagation On Signed Networks

The formation of public opinion on the network is a hot issue in the field of complex network research, and some classical dynamic models are used to solve this problem. The signed network is a particular form of the complex network, which can adequately describe the amicable and hostile relationships in complex real-world systems. However, the methods for studying the dynamic process of public opinion propagation on signed networks still require to be further discussed. In this paper, the authors pay attention to the influence of negative edges in order to design a two-state public opinion propagation mechanism suitable for signed networks. The authors first set the interaction rules between nodes and the transition rules of node states and then apply the model to synthetic and real-world signed networks. The simulation results show that there is a critical value of the negative edge ratio.When the negative edge ratio exceeds this critical value, the evolutionary result of public opinion will change from a consistent state to a split state. This conclusion is also consistent with the distribution result of opinions within communities in the signed network. Besides, the research on the network structural balance shows that the model makes the network evolve in a more balanced direction.     

Optimally Connected Hybrid Complex Networks with Windmill Graphs Backbone

The significance of the existing analysis methods in complex networks and easy access to the ever-increasing volume of information present the emergence of proposing new methods in various fields based on complex system ideas. However, these systems are usually faced with various random failures and intelligent attacks. Due to the nature of the components' behaviors, the occurrence of the failures and faults in their operations and the alteration of their topologies are the most important problems. Since the complex systems are usually used as the infrastructures of other networks, their robustness against failures and the adoption of suitable precautions are necessary. Moreover, the smallworld effect in most complex systems is one of the crucial structural features. The authors found that the relation between these two is not well-known and may even be in conflict in some networks. The main goal in this paper is to achieve an optimal topology by utilizing a robustness-oriented multiobjective trade-off optimization model(edge rewiring) to establish a peaceful relationship between the two requirements. By offering a proposed rewiring method with the small-world effect, which is called core-periphery Windmill property, the authors demonstrated that the generated networks are able to exhibit appropriate robustness even during intelligent attacks. The results obtained in terms of Windmill graphs are presented very good approximations to demonstrate the small-world effect. These graphs are used as the initial core in the construction of the optimized networks' topologies.     

无线传感器网络的混合抗干扰攻击方法

为对抗无线传感器网络中存在的强针对性的智能型干扰攻击,基于多种扩频技术提出了一种混合跳频扩频、非协调直接序列扩频以及非协调跳频扩频的抗干扰攻击方法。为解决传统扩频技术需要提前共享密钥的限制,在网络初始化阶段使用非协调跳频扩频进行网络通信;为避免持续使用非协调扩频跳频带来的高能量消耗问题,发送节点与接收节点在非协调扩频跳频模式下生成跳频序列,即可进行传统跳频扩频;通过非协调直接序列扩频技术进一步增强对抗干扰攻击的性能;使用OPNET并基于多种干扰攻击模型进行网络仿真,评估所提出的混合抗干扰攻击方法的性能。仿真结果表明,在环境恶劣情况下,并受到强针对性的智能型干扰攻击时,网络仍能保持较低的丢包率,故所提出的混合抗干扰攻击方法能有效地抵抗无线传感器网络中的干扰攻击。     

Sensor selection for random field estimation in wireless sensor networks

This paper studies the sensor selection problem for random field estimation in wireless sensor networks.The authors first prove that selecting a set of l sensors that minimize the estimation error under the D-optimal criterion is NP-complete.The authors propose an iterative algorithm to pursue a suboptimal solution.Furthermore,in order to improve the bandwidth and energy efficiency of the wireless sensor networks,the authors propose a best linear unbiased estimator for a Gaussian random field with quantized measurements and study the corresponding sensor selection problem.In the case of unknown covariance matrix,the authors propose an estimator for the covariance matrix using measurements and also analyze the sensitivity of this estimator.Simulation results show the good performance of the proposed algorithms.     

Generating semi-algebraic invariants for non-autonomous polynomial hybrid systems

Hybrid systems are dynamical systems with interacting discrete computation and continuous physical processes, which have become more common, more indispensable, and more complicated in our modern life. Particularly, many of them are safety-critical, and therefore are required to meet a critical safety standard. Invariant generation plays a central role in the verification and synthesis of hybrid systems. In the previous work, the fourth author and his coauthors gave a necessary and sufficient condition for a semi-algebraic set being an invariant of a polynomial autonomous dynamical system, which gave a confirmative answer to the open problem. In addition, based on which a complete algorithm for generating all semi-algebraic invariants of a given polynomial autonomous hybrid system with the given shape was proposed. This paper considers how to extend their work to non-autonomous dynamical and hybrid systems. Non-autonomous dynamical and hybrid systems are with inputs, which are very common in practice; in contrast, autonomous ones are without inputs. Furthermore, the authors present a sound and complete algorithm to verify semi-algebraic invariants for non-autonomous polynomial hybrid systems. Based on which, the authors propose a sound and complete algorithm to generate all invariants with a pre-defined template.     

Caveman网络及其在复杂网络熵分析中的应用

熵可以有效反映复杂系统内网络结构的异质性.针对熵指标在刻画网络全局异构上是否适用这一问题,目前仍缺少用以评测的基准网络.对此,在已有结构熵研究的基础上,提出一种Caveman网络构造及其演化规则,为网络复杂性的度量提供新的思路。通过数理分析和仿真实验验证该Caveman网络可以有效评测各类结构熵指标对其演化过程的敏感性,反映熵指标对网络复杂特征识别能力的差异。同时由于Caveman网络可以更好地探索信息空间和抵御攻击,将有助于设计鲁棒、高效的系统结构。     

基于模糊层次分析的小小区性能评估

小小区的引入大幅提高了蜂窝网络的覆盖和容量,同时也带来了更复杂的无线环境。提出了一种基于改进的模糊层次分析（fuzzy analytic hierarchy process, FAHP）的小小区性能评估方法;建立了小小区层次结构模型;分析了影响小小区性能的影响因素,并结合模糊数学原理提出相应的指标测量及量化方法;改进了模糊层次分析法的权重计算方法,在此基础上得出各小小区方案性能评估结果。仿真结果表明,提出的方法能在不同的小小区配置方案中选择出最优方案,为小小区的设计与部署提供参考。     

下一代密集WLAN网络干扰管理机制

在密集高效无线局域网部署场景中,针对传统802.11协议造成用户公平性差和吞吐量低的问题,提出一种以用户为中心的资源配置方法。该方法通过对用户进行识别分类,以用户为中心配置信道和功率,在保证用户公平性的前提下,最大化网络吞吐量。提出的功率控制机制和用户识别方法可以很简单的应用于现有无线局域网系统中。仿真结果表明,提出的资源配置方法平均提升单位基本服务集吞吐量47.3%,干扰最严重的基本服务集的吞吐量提升190%,每个基本服务集的边缘用户的吞吐量平均提升约74.3%。     

QoS-aware multicast routing protocol for Ad hoc networks

1 .INTRODUCTIONA mobile ad hoc network ( MANET) is a multi-hopwireless network formed by a collection of mobilenodes without the intervention of fixedinfrastructure.Because an Ad hoc network is infrastructure-less andself-organized,it is used to provide i mpromptu com-munication facilities in harsh environments . Typicalapplication areas of mobile ad hoc networkinclude bat-tlefields ,emergency search,rescue sites and data ac-quisitionin remote areas . A mobile Ad hoc networkisalso usef…     

多无人机自主编队协同制导技术的概念、设计和仿真

现代防空技术的迅速发展使得制导武器的突防效果大大下降,多飞行器自主编队协同制导技术成为提高未来制导武器作战效能的关键技术之一.定义了高动态自主编队协同制导技术的概念体系;提供编队队形生成、队形保持和控制、协同导航与航路规划、目标协同捕捉与动态分配、协同末制导等关键技术的框架结构和设计方法:并设计了适用于自主编队协同制导技术的无线自组织网络结构和组网协议,实现高动态环境下信息的互联、互通和互操作,且节点具备自主管理能力和容错能力;通过所构建的多UAV自主编队协同制导验证演示系统验证表明,系统的框架结构和设计方法有效,系统性能满足技术指标要求.     

Complex cyber-physical networks: From cybersecurity to security control

Complex cyber-physical network refers to a new generation of complex networks whose normal functioning significantly relies on tight interactions between its physical and cyber components. Many modern critical infrastructures can be appropriately modelled as complex cyber-physical networks. Typical examples of such infrastructures are electrical power grids, WWW, public transportation systems, state financial networks, and the Internet. These critical facilities play important roles in ensuring the stability of society as well as the development of economy. Advances in information and communication technology open opportunities for malicious attackers to launch coordinated attacks on cyber-physical critical facilities in networked infrastructures from any Internet-accessible place. Cybersecurity of complex cyber-physical networks has emerged as a hot topic within this context. In practice, it is also very crucial to understand the interplay between the evolution of underlying network structures and the collective dynamics on these complex networks and consequently to design efficient security control strategies to protect the evolution of these networks. In this paper, cybersecurity of complex cyber-physical networks is first outlined and then some security enhancing techniques, with particular emphasis on safety communications, attack detection and fault-tolerant control, are suggested. Furthermore, a new class of efficient secure control strategies are proposed for guaranteeing the achievement of desirable pinning synchronization behaviors in complex cyber-physical networks against malicious attacks on nodes. The authors hope that this paper motivates to design enhanced security strategies for complex cyber-physical network systems, to realize resilient and secure critical infrastructures.     

Dynamically Optimized Sensor Deployment Based on Game Theory

Sensor network deployment is the key for sensors to play an important performance. Based on game theory, first, the authors propose a multi-type sensor target allocation method for the autonomous deployment of sensors, considering exploration cost, target detection value, exploration ability and other factors. Then, aiming at the unfavorable environment, e.g., obstacles and enemy interference, the authors design a method to maintain the connectivity of sensor network, under the conditions of effective detection of the targets. Simulation result shows that the proposed deployment strategy can achieve the dynamic optimization deployment under complex conditions.     

基于异步动态的多机器人系统的一致性

研究通过无线网络进行通信的多机器人系统的一致性问题。多机器人系统在固定通信拓扑下可建模为特定的网络控制系统,考虑信道噪声、不确定短时延和数据包丢失等因素的影响时,其可进一步视作由丢包率约束的异步动态系统。通过构造李雅普诺夫(Lyapunov)函数,运用线性矩阵不等式(linear matrix inequality, LMI)方法,得到了该系统指数稳定的充分条件。为实现多机器人系统的运动一致性,设计了控制器；讨论了不同的指数收敛率对多机器人系统收敛速度的影响,并进行了相应的理论证明和仿真验证。     

基于负熵最大化的压缩感知信道估计算法

讨论了在5G时代随着移动终端和网络流量的增长、大规模机器类型通信的产生以及天基卫星网络与地面蜂窝主干网络的结合, 使得移动无线通信的频谱使用范围更宽, 导致信道具有更为明显的稀疏性, 从而得以利用无线信道的稀疏性引入压缩感知技术来进行无线通信系统的信道估计。通过负熵最大化算法与l_p正则化改进现有的压缩感知信道估计算法, 将传统的最小化误差函数均方误差替代为最大化目标函数的负熵以适应信道非高斯噪声, 同时稀疏约束采用更为精确的l_p正则化以加强信道估计算法的稀疏表示。研究表明, 该算法不仅可以提高信道估计精度, 增强抗噪声鲁棒性; 另一方面可以利用更少的导频实现更高精度的信道估计, 具备提高系统频谱利用率的作用。