一种无线传感器网络选择转发攻击检测法研究

研究了无线传感器网络安全问题,由于网络容易受到攻击,针对无线传感器网络受到攻击丢失信息的缺陷,深入分析各种攻击的特征,为改善对选择转发攻击的检测效率,提出了一种基于检查点的多跳确认方案,可能够随机地选取传递路径中的部分节点为检查点,负责包的确认,提高检测效率.随机检查点选择技术能够避免部分节点成为敌方俘获的目标.进行仿真,结果表明,能在在保证检测能力的同时有效地提高了系统的健壮性,对网络整体安全的提高有实际意义.     

一种基于IBE的WSNs选择转发攻击检测方案

无线传感器网络因节点能力的限制,通常采用多跳的方式进行节点间消息的互发,这种多跳路由协议为选择转发攻击提供了便利。基于此,提出一种基于随机检查点的多跳确认方案来检测无线传感器网络中的选择转发攻击,将IBE加密及LEACH路由协议引入其中,用以对选择转发攻击的检测方法加以改进。给出检测防御方案的总体框架,对其工作方式进行了具体描述。在NS2环境下,从检测点数目、计算速度与能耗、存储要求及健壮性等几方面对改进方案进行了仿真,以验证其对无线传感器网络安全性的提高。     

无线传感器网络中定位攻击防范

论文提出一种基于检查点、区域投票机制和轻量级安全协议的传感器网络节点定位安全措施。该方案采用隔离恶意信标的策略来提高定住系统抵抗攻击的能力,无需针对每种可能出现的特定攻击行为进行一一防范,从而简化了安全策略的实施。文章对防范方案的检测率进行了理论分析。     

无线传感器网络选择性传递攻击的检测和防御机制

针对无线传感器网络的选择性转发攻击,以提高恶意节点检测率和系统防御性为目标,提出了一种基于最优转发策略的随机路由算法和可信邻居节点监听的检测和防御方法。该方法通过引入距离、信任度等参数构建转发路径,同时,在路由发现和选择过程中,采用节点监听机制对恶意节点进行检测和防御处理。在Matlab环境下对该机制进行了仿真实验,并与其他方法进行了性能对比分析。实验结果表明：该方法能够在消耗相对较少能量情形下有效检测出选择性传递攻击,保持较高事件报文成功率,并且对恶意节点能做到有效的防御和处理。     

一种基于多跳确认和信任评估的选择性转发攻击检测方法

针对无线传感器网络中的选择性转发攻击行为,提出一种基于多跳确认和信任评估(MHA-TE)的选择性转发攻击检测方法.MHA-TE方法利用基于源节点的请求响应形式的多跳确认方案,通过源节点发送请求包、中间节点回复响应包的方式确定路径中产生恶意丢包行为的节点,进而将被检举出的恶意节点作为信任评估的参数更新标准,运用Bate分布建立信任评估模型分析各个节点的交互情况,确定路径中各节点的信任值,并将更新后的信任值与对应的信任值阈值比较,进行恶意节点的判定.该方法结合多跳确认和信任评估的优势,能够解决路径上多恶意节点误警率高和静态信任阈值适应性差以及检测率低的问题.仿真实验结果表明,相比于Two-hops方法、MLCM方法和ITEM方法,MHA-TE方法不仅能够有效检测恶意节点,具有较高的检测率和较低的误警率,而且可以在很大程度上降低网络开销.     

基于平均海明距离的WSN安全路由算法

提出一种基于平均海明距离的无线传感器网络安全路由算法。该算法利用节点的实时包传递率短序列和正常运行短序列之间的平均海明距离,检测节点是否正常。在节点中引入邻近节点表,对恶意节点进行隔离,在重新组簇的过程中节省节点能量,在路由选择时综合考虑能量、跳数和路径可靠性等因素。仿真实验结果表明,该算法能耗较低,具有较高的检测率。     

一种射频能量捕获无线传感器网络的分层分步数据收集策略

在射频能量捕获无线传感器网络中,采用多跳的方式将数据发送给网络中的Sink节点能够减少节点间的通信距离,从而减少能量的消耗,但增加了转发节点的收发数据量。为了减少网络中转发节点的负载,延长网络的生命周期,提出了一种分层分步的数据收集方法(Layer-Step Data Collection,LSDC)。通过对网络中节点能量进行捕获和在能量消耗过程进行建模,得到节点的剩余能量。通过运用多次“跳”命令的方式通知网络中的传感器节点分步地将采集到的数据传递给Sink节点。在传递节点的选择上,以能量状况最佳的节点作为传递节点,最终达到高效地将网络中的数据全部收集到Sink节点进行处理的目的。理论分析与仿真实验结果表明,与采用逐层收集数据的方法(Layer-By-Layer Data Collection,LDC)相比,所提方案更节能,能量消耗更均衡,能够延长网络的生命周期。     

隐式路由协议的一种转发节点快速选择算法

针对已有隐式路由协议转发节点选择算法效率不高的缺点，提出了一种基于IEEE 802.11 DCF机制的转发节点快速选择算法（FFS）．该算法让候选转发节点根据自己的转发优先级退避相应的时隙后发送CTS帧，并在多个候选节点发生冲突时随机选择退避时隙值，从而快速高效地唯一确定转发节点．仿真结果表明，FFS算法在能效、时延、分组到达率等网络性能指标上优于已有算法．     

基于最优转发策略的无线传感器网络随机路由协议

提出一种基于地理信息的随机路由协议,该协议以优化参数选择候选路由节点.为确定候选路由节点数据转发的优先级,引入数据包传递期望值EPA.EPA综合考虑了链路质量以及数据包传递的距离,确定离目的节点越近的候选节点数据转发的优先级越高.经过理论分析,该转发策略能够使EPA取得最大值,是一种局部最优策略.仿真实验结果表明,该协议在数据传输延迟和数据吞吐率等方面明显优于地理路由协议.     

WSN中基于粒子滤波的入侵检测算法实现

安全问题已经成为无线传感器网络进一步发展和应用的障碍之一。文章提出了一种基于粒子滤波算法的入侵检测技术,该方案利用LEACH算法对无线传感器网络节点进行分簇,通过粒子滤波算法对簇内节点的数据流量情况进行检测,发现其中的异常节点,并利用MATLAB仿真工具对节点的反应灵敏度进行仿真。结果表明,算法计算得出的异常检测率维持在0.48到0.7之间,检测系统处于一种较为稳定的状态,粒子滤波能够较好的运用到WSN的入侵检测系统中。     

Rethinking the architecture design of data center networks

In the rising tide of the Internet of things, more and more things in the world are connected to the Internet. Recently, data have kept growing at a rate more than four times of that expected in Moore’s law. This explosion of data comes from various sources such as mobile phones, video cameras and sensor networks, which often present multidimensional characteristics. The huge amount of data brings many challenges on the management, transportation, and processing IT infrastructures. To address these challenges, the state-of-art large scale data center networks have begun to provide cloud services that are increasingly prevalent. However, how to build a good data center remains an open challenge. Concurrently, the architecture design, which significantly affects the total performance, is of great research interest. This paper surveys advances in data center network design. In this paper we first introduce the upcoming trends in the data center industry. Then we review some popular design principles for today’s data center network architectures. In the third part, we present some up-to-date data center frameworks and make a comprehensive comparison of them. During the comparison, we observe that there is no so-called optimal data center and the design should be different referring to the data placement, replication, processing, and query processing. After that, several existing challenges and limitations are discussed. According to these observations, we point out some possible future research directions.     

Currents in connectionism

This paper reviews four significant advances on the feedforward architecture that has dominated discussions of connectionism. The first involves introducing modularity into networks by employing procedures whereby different networks learn to perform different components of a task, and a Gating Network determines which network is best equiped to respond to a given input. The second consists in the use of recurrent inputs whereby information from a previous cycle of processing is made available on later cycles. The third development involves developing compressed representations of strings in which there is no longer an explicit encoding of the components but where information about the structure of the original string can be recovered and so is present functionally. The final advance entails using connectionist learning procedures not just to change weights in networks but to change the patterns used as inputs to the network. These advances significantly increase the usefulness of connectionist networks for modeling human cognitive performance by, among other things, providing tools for explaining the productivity and systematicity of some mental activities, and developing representations that are sensitive to the content they are to represent.A version of this paper was the invited address at the first annual conference of the Society for Machines and Mentality in December, 1991. A related version was presented at the Computers and Philosophy Conference in August, 1992. I am extremely grateful to Adele Abrahamsen for her numerous suggestions and comments on various drafts of this paper.     

复杂网络聚类算法在生物网络中的应用

复杂网络在现实世界中普遍存在,具有小世界性和无标度性等统计特性,网络簇结构是复杂网络重要的拓扑属性之一。在复杂生物网络中使用聚类算法揭示生物网络中的簇结构对分析生物网络的拓扑结构、预测其功能都具有重要意义。对复杂网络聚类方法在蛋白质-蛋白质相互作用网络和新陈代谢网络中的应用及其进展情况进行了综述,分析了几种聚类算法的评价函数和适用条件,并对生物网络聚类算法研究所面临的主要问题进行了讨论。     

因子分解二终端网络可靠度近似计算

因子分解算法可以用来计算网络可靠度精确值,但对于大型网络,可靠度精确值的计算非常困难。基于时间和精确度的双重考虑,在精确算法的基础上通过改进得出一种近似算法。实验结果证明,该算法得到的近似值接近精确值,而且计算时间要低于精确算法。     

A middleware for industry

This paper describes an innovative distributed framework for monitoring and control of large-scale systems by integrating heterogeneous smart objects, the world of physical devices, sensors and actuators, legacy devices and sub-systems, cooperating to support holistic management [1]. Its featured Service Oriented Architecture (SOA) exposes objects’ capabilities by means of web services, thus supporting syntactic and semantic interoperability among different technologies, including SCADA systems [23]. Wireless Sensor and Actuator Network (WSAN) devices and legacy subsystems cooperate while orchestrated by a manager in charge of enforcing a distributed logic. Particularly crafted for industrial networks are new middleware services such as dynamic spectrum management, distributed control logic, object virtualization, WSANs gateways, a SCADA gateway service, and data fusion transport capability. In addition, new application oriented objects such as shop floor, manufacturing line, welding station, robots, and cells have been introduced in the middleware. The combination of such objects and previous modules offers a new and flexible industry oriented middleware. A second contribution is in the form of traffic analysis conducted at the floor level. It shows the dominance of some end systems such as PLCs, the presence well behaved almost constant traffic made up of small packets.     

A new routing algorithm for multirate rearrangeable Clos networks

In this paper, we study the problem of finding routing algorithms on the multirate rearrangeable Clos networks which use as few number of middle-stage switches as possible. We propose a new routing algorithm called the “grouping algorithm”. This is a simple algorithm which uses fewer middle-stage switches than all known strategies, given that the number of input-stage switches and output-stage switches are relatively small compared to the size of input and output switches. In particular, the grouping algorithm implies that m = 2n+(n−1)/2^k is a sufficient number of middle-stage switches for the symmetric three-stage Clos network C(n,m,r) to be multirate rearrangeable, where k is any positive integer and rn/(2^k−1).     

无线有组织网络

无线有组织网络是网络节点间有内在关系的无基础设施的无线网络,其除具有无基础设施无线网络的特征外,网络有中心节点,且节点位置关系相对固定。这种特殊的网络应用于野外救援、军事活动等临时性通信。首先回顾了对讲机系统、无线分组网络和无线自组织网络等无基础设施无线网络的结构和特点,它们都不能包涵无线有组织网络特征。详细定义了无线有组织网的相关模型,分析了无线有组织网络的特点和研究重点。     

Banet — a local area network for distributed data processing

A broadcast architecture network (Banet) suitable for distributed data processing is proposed. One feature of Banet is that the broadcast-within-a-group function is supported not only by the datalink level but by the transport or session-level network structure. The commitment control scheme is included in the network protocol. Design goals, physical structure and protocols are discussed.     

多层前向小世界神经网络及其函数逼近

借鉴复杂网络的研究成果, 探讨一种在结构上处于规则和随机连接型神经网络之间的网络模型—-多层前向小世界神经网络. 首先对多层前向规则神经网络中的连接依重连概率p进行重连, 构建新的网络模型, 对其特征参数的分析表明, 当0 < p < 1时, 该网络在聚类系数上不同于Watts-Strogatz 模型; 其次用六元组模型对网络进行描述; 最后, 将不同p值下的小世界神经网络用于函数逼近, 仿真结果表明, 当p = 0:1时, 网络具有最优的逼近性能, 收敛性能对比试验也表明, 此时网络在收敛性能、逼近速度等指标上要优于同规模的规则网络和随机网络.     

神经网络控制结构及所用神经网络

本文阐述了神经网络控制所能解决的控制难题，若干种控制结构及常用的动态神经网络。讨论了神经网络控制研究的重点，在实时控制中的物理可实现性及其发展等问题。