面向恶意程序传播的传感网可靠度评估

为评估恶意程序传播环境中的传感网可靠度,引入"死亡"状态扩展了传统的SEIR传染病模型,采用马尔可夫链确切地描述了传感节点的状态动态变化过程.利用随机博弈,提出了传感网恶意程序传播检测模型来预测恶意程序的传播行为概率,再将得到的结果整合到马尔可夫链的状态转换矩阵,实现了恶意程序传播故意性和马尔可夫链随机性的关联.建立了利用马尔可夫链计算恶意程序传播环境中传感节点可靠度的公式,分别给出了具有星形和簇状拓扑结构的传感网可靠度评估方法.实验给出了恶意程序传播对传感节点可靠度的影响,结果表明所提出的方法能有效评估整个传感网的可靠度.     

雷达系统使用可用度计算机仿真计算

系统可用度是可靠性和维修性的综合反映 ,常用的马尔可夫方法无法给出可修复机电产品的系统可用度计算公式。给出了一种计算双机冷储雷达系统使用可用度的计算机仿真方法示例 ,并可将它推广至一般机电产品的可用度计算。     

云场景下天基红外探测可用度快速评估

天基红外探测场景下,云的存在会对目标探测造成严重干扰,导致无法连续检测跟踪目标,降低系统探测效能。系统在凝视工作模式下,背景在一段时间周期内变化较小,可根据背景特性建模分析不同云场景下探测系统的可用度。将理论分析、图像仿真、解析建模等多种手段相结合,对云场景下天基红外探测可用度进行快速评估。首先通过对目标穿越云层时的信杂比变化进行分析,建立可用度的初步估计模型,确定可用度的影响因素。然后在图像仿真和解析建模中,基于仿真结果拟合了信杂比低于阈值图像帧数跟云参数之间的线性关系,并结合参数物理含义建立可用度解析模型,采用回归分析法确定模型系数。最后基于新的仿真工况对比天基红外探测可用度的仿真值、初步估计值和解析预测值,验证模型的准确性和鲁棒性,该模型可作为系统可用度效能评估的有益参考。     

社区结构感知的间断连接无线网络路由机制

针对间断连接无线网络中消息投递成功率低的问题1依据网络中节点社会关系的差异性,提出了一种社区结构感知的路由机制.该机制根据节点在各个运动周期内的状态信息建立马尔可夫模型,以描述节点运动状态转换过程,进而以分布式的方式感知节点中心度,并以社区中心度为参数,采用社区标签交换方法对网络结构进行动态检测,最终利用社区内中心节点为中继辅助完成消息的转发.仿真结果表明,所提出的路由机制在投递率方面的性能改善程度接近90％,极大地优化了网络性能.     

基于隐马尔可夫模型的风险评估方法

针对网络攻击场景下一段时间内信息系统面临的安全风险,文中提出一种基于隐马尔可夫模型的风险评估方法,将网络主机的漏洞建模为隐马尔可夫模型中的状态,将可能受到的攻击建模为隐马尔可夫模型中的观察值,求解一段时间内的成功攻击概率;根据攻击成功后产生的代价和成功攻击的概率,得到时间段内总风险度量值。该方法可从整体角度对网络攻击场景下一段时间内的信息安全风险进行量化评估。     

成批维修策略下雷达冗余系统可用度研究

某些大型相控阵雷达中，装备设备量大与要求装备可用度高之间存在很大矛盾，如何在装备采用冗余设计和备件批量送修的条件下，最大限度地提高装备的使用可用度，是雷达保障方案制定面临的难点问题。针对该难题，本文通过建立定期成批维修策略下雷达冗余系统的使用可用度模型，求解雷达使用可用度模型，分析某雷达阵面的使用可用度实例，最终明晰了使用可用度与系统停机前工作时间、初始备件数量、部件维修人员数量三个因素的关系。结果表明，该模型可以优化备件、维修人员等保障资源的配置，为雷达冗余系统维修保障方案的制定提供支持。     

基于灰色层次分析法的DS/FH测控系统可用度评估

针对干扰环境下DS/FH测控系统可用度的问题,提出运用灰色层次分析法进行评估的方法:通过层次分析法确定指标的权重,通过灰色白化函数确定指标的白化值,通过加权求和确定系统的可用度值,通过不同指标的抗干扰裕量确定可用度的模糊评价集,最后通过实例验证了评估方法的可行性。     

一种计算可修复网络可用度的快速算法

对于可修复系统,其状态数随系统规模呈指数增长。文中在系统元件类型相同的假设条件下,以维修顺序为突破口剖析马尔可夫模型,证明在某几种维修顺序条件下,可由类状态概率来计算类状态中单个状态的概率;并以可修复网络系统为例提出了从类状态到不交和状态的映射算法,从而使计算网络可用度的复杂度大大降低。仿真结果表明合并策略和映射算法的正确。     

基于Markov过程的硬/软件综合系统可靠性分析

现代大型监控系统通常是一个复杂的硬/软件综合系统,其可靠性分析对于系统的设计、评估具有重要意义.综合考虑硬件、软件特点以及两者之间的相互作用关系,提出一种基于Markov过程的综合系统可靠性分析模型,模型中将系统失效分为硬件失效、软件失效与硬/软件结合失效.实际应用中,由于系统的状态数较大,提出利用循环网络方法对Markov状态转移方程进行求解,从而方便地得到系统处于各状态的瞬时概率与稳态概率.通过分析硬/软件综合系统可靠度、可用度与系统可靠性参数之间的关系,指出硬/软件结合失效将影响系统可用度,忽略硬/软件结合失效将导致可靠性估计值偏离实际值.     

联机检修的冗余结构使用可用度模型修正

现场故障更换对象由电子和机电元器件改变为电子和机电更换模块后,备件保障就成为联机检修冗余结构任务可靠度和使用可用度模型中必须包含的一个关键参数。但在传统的联机检修任务可靠度和现行的使用可用度模型中没有得到或没有完全得到应有的反映。对此,提出了修正模型。在使用可用度模型中还对同时检修的平均修复时间模型作出了改正。     

基于DTMC建模和分析的障碍Ad hoc网络

One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discrete-time Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.     

基于马氏链的数据链网络抗毁性评价方法

针对数据链网络抗摧毁问题,提出了基于网络拓扑图的马氏链模型。指出若网络中存在经过奇数次跳转能够回到自己的节点时,此网络图的马氏链是遍历的,且其极限概率为该节点的度比上所有节点度之和。然后根据上述模型,提出把其他节点以最短路径到达该节点概率之和作为节点重要性评判指标。在此基础上,把待评价网络与全联通网络的进行结构差异比较作为抗毁性的评价方法。实例验证了模型与算法的有效性。     

FUCEM: futuristic cooperation evaluation model using Markov process for evaluating node reliability and link stability in mobile ad hoc network

The cooperation between the nodes is one of the potential factor for successful routing in mobile ad hoc networks. The non-cooperative behaviour of the node disturbs the routing as well as degrades network performances. The non-cooperativeness is due to the resource constraint characteristics of a mobile node. The battery energy is an important constraint of a node because it exhausts after some period. On the other side, the mobility of nodes also affects routing performances. Hence, this work concentrates on evaluating cooperation of a node by probing future node energy and mobility. This paper proposes a futuristic cooperation evaluation model (FUCEM) for evaluating node reliability and link stability to establish effective routing. The FUCEM model examines influencing factors of cooperation and state transition of nodes using Markov process. Node reliability and link stability manipulated through the Markov process. The Markov process helps in fixing the upper and lower bounds of the cooperation and calculates the cooperation factor. The NS2 simulator simulates the proposed work and evaluates performance results with different scenarios. The result indicates that the proposed FUCEM has 13–21% higher packet delivery ratio than other algorithms. The remaining energy of the nodes increases to 6–7% as compared with the existing algorithms in a higher mobility scenario. Further, it significantly improves the results of routing overhead and average end-to-end delay than the existing models.

     

DTN 网络环境下动态随机网络编码方法简

容迟容断网络的移动性、间歇连通性和动态拓扑等动态特性使得当前应用于静态网络拓扑和固定多播容量的静态随机网络编码难以适应DTN网络环境的网络编码传输,为此提出了一种DTN网络环境下动态随机网络编码传输方法。该方法以马尔科夫信道模型为基础,根据节点的数据状态动态监测信道速率,在信源节点构造了带信道容量的网络流图,并计算和预测当前网络多播容量,最后根据多播容量的变化动态扩展和裁剪随机网络编码方案,实现DTN网络环境下数据的动态网络编码传输。仿真结果表明,相比传统的固定多播率编码方法,动态随机网络编码方法降低了数据的平均传递延迟,提高了数据投递率。     

Lightweight opportunistic routing forwarding strategy based on Markov chain

A lightweight opportunistic routing forwarding strategy (MOR) was proposed based on Markov chain.In the scheme,the execute process of network was divided into a plurality of equal time period,and the random encounter state of node in each time period was represented by activity degree.The state sequence of a plurality of continuous time period constitutes a discrete Markov chain.The activity degree of encounter node was estimated by Markov model to predict its state of future time period,which can enhance the accuracy of activity degree estimation.Then,the method of comprehensive evaluating forwarding utility was designed based on the activity degree of node and the average encounter interval.MOR used the utility of node for making a routing forwarding decision.Each node only maintained a state of last time period and a state transition probability matrix,and a vector recording the average encounter interval of nodes.So,the routing forwarding decision algorithm was simple and efficient,low time and space complexity.Furthermore,the method was proposed to set optimal number of the message copy based on multiple factors,which can effectively balance the utilization of network resources.Results show that compared with existing algorithms,MOR algorithm can effectively increase the delivery ratio and reduce the delivery delay,and lower routing overhead ratio.     

Transmission scheduling scheme based on deep Q learning in wireless network

To cope with the problem of data transmission in wireless networks,a deep Q learning based transmission scheduling scheme was proposed.The Markov decision process system model was formulated to describe the state transition of the system.The Q learning algorithm was adopted to learn and explore the system states transition information in the case of unknown system states transition probability to obtain the approximate optimal strategy of the schedule node.In addition,when the system state scale was big,the deep learning method was employed to map the relation between state and behavior to solve the problem of the large amount of computation and storage space in Q learning process.The simulation results show that the proposed scheme can approach the optimal strategy based on strategy iteration in terms of power consumption,throughput,packets loss rate.And the proposed scheme has a lower complexity,which can solve the problem of the curse of dimensionality.     

Dynamic cache allocation routing strategy of Internet of things satellite node based on traffic prediction

Aiming at the routing problem of low earth orbit (LEO) Internet of things (IoT) satellite systems,a dynamic cache allocation routing strategy based on traffic prediction for IoT satellite nodes was proposed.Firstly,the space-time characteristics of traffic distribution in the LEO coverage area were analyzed,and an end-to-end traffic prediction model was proposed.Then,according to the traffic prediction result,a dynamic cache allocation routing strategy was proposed.The satellite node periodically monitored the traffic load of the inter-satellite link,dynamically allocated the cache resources of each inter-satellite link between the neighboring nodes.The cache allocation process was divided into two phases,initialization and system operation.At the same time,the traffic offload and packet forwarding strategy when the node was congested was proposed.By comparing the queuing delay and the forwarding delay,it was determined whether the data packet needs to be rerouted.The simulation results show that the proposed routing strategy effectively reduces the packet loss rate and average end-to-end delay,and improves the traffic distribution in the whole network.     

基于PCN的水下认知网络动态频谱接入算法

水下网络可用频谱范围比较窄,且部分被水下生物占用,导致了水下传感器网络可用的频谱资源更为稀缺.针对上述问题,提出一种基于累积干扰预测(Predicted Cumulative Noise,PCN)的水下认知网络动态频谱接入算法.该算法把水下生物作为认知网络的主节点,水下传感器节点作为次节点;通过建立水下生物业务行为的马尔科夫模型预测累积干扰,次节点根据预测结果,采用合作的方式动态地接入授权频谱.仿真结果表明,该算法能够保护水下生物正常通信的同时,实现最优化的频谱共享,网络容量增益达到6.3dB.     

Survivability Performance Evaluation of WDM Networks with Wavelength Converters

Network Survivability is defined as the ability of a network to support the committed Quality of Services (QoS) continuously in the presence of different failure scenarios. Both availability and performance degradation of a system in presence of failure are integral components of survivability evaluation. Therefore, a composite model is presented for network survivability that includes system availability analysis to find out the cost due to system downtime, and system failure impact analysis to find out the transient performance degradation when failure occurs. A new analytical technique is presented to evaluate the excess loss due to failure (ELF) as the transient performance degradation when the system is operating in gracefully degraded states. Single and multiple link failures as well as node failures are considered. An algorithm is proposed to carry out the steady state availability analysis of a network even when the available paths between a pair of nodes are non-disjoint. A recursive generalized form of the availability algorithm when there are multiple paths available between a pair of nodes is presented. The availability model and the performance model are combined to construct a hierarchical model to evaluate the network survivability performance. Simulation results are used to validate the proposed model. A WDM network with wavelength conversion is considered as an example for this evaluation.