基于透传的IPv6个人区域网无线网关设计

主干网络设备和操作系统支持IPv6协议的请况下,大量的个人区域网网关仅使用IPv4地址转换的方式连接互联网,不能支持IPv6,提出一种数据链路层透传的数据包处理方式,使IPv6数据直接通过网关,减少地址转换或者中间代理的过程,实现内部网直接接入IPv6网络。经分析和实验,该设计方法在不影响IPv4使用的情况下使个人区域网内部设备顺利接入IPv6网络。     

A Secure Adaptive Routing Strategy Using Immune Mechanism in MANET

Many protocols have been proposed to in- crease efficiency and security of traditional protocols in Mobile ad-hoc networks （MANET）, but they are all facing the problem of computation overhead which leads to im- practicability. Adaptive routing strategy （ARS） is a novel routing strategy that switches routing protocol according to the network condition. Though this method alleviates the problem of efficiency, it doesn＇t cover the secure issues. We integrate our security mechanism based on Artificial immune system （AIS）, with adaptive routing strategy to enhance efficiency and security. First we presented a more appropriate definition to the measurement of network con- dition, then we designed a secure adaptive routing strategy based on the definition. At last, we gave a performance analysis to validate the correctness and reliability of our scheme.     

An Optimization Forwarding Range Routing Protocol for VANET in City Environments

In city environment, the vehicle communi- cation is affected by the around obstacles due to the espe- cial condition of wireless channels. However, most of prior works adopt the fixed radio range value of vehicles to trans- mit packets. In this paper, we design an optimization for- warding range routing protocol for VANET in urban area. It has an optimized and adjustable forwarding range, which changes with different environments based on the path loss and the city model. And the proposed geo-routing protocol has a novel idea in computing the connectivity of roads and the adjustable strategy in a sparse network. Simulation re- suits indicate that the OFRR enjoys desirable performance in the urban area.     

Routing and mobility approaches in IPv6 over LoWPAN mesh networks

It is foreseeable that any object in the near future will have an Internet connection—this is the Internet of Things vision. All these objects will be able to exchange and process information, most of them characterized by small size, power constrained, small computing and storage resources. In fact, connecting embedded low‐power devices to the Internet is considered the biggest challenge and opportunity for the Internet. There is a strong trend of convergence towards an Internet‐based solution and the 6LoWPAN may be the convergence solution to achieve the Internet of Things vision. Wireless mesh networks have attracted the interest of the scientific community in recent years. One of the key characteristics of wireless mesh networks is the ability to self‐organize and self‐configure. Mesh networking and mobility support are considered crucial to the Internet of Things success. This paper surveys the available solutions proposed to support routing and mobility over 6LoWPAN mesh networks. Copyright © 2011 John Wiley & Sons, Ltd.     

一种基于多穴跳变的IPv6主动防御模型

该文利用IPv6多穴技术,借鉴跳频通信的跳变思想,提出多穴跳变的概念,将主机的地址在网络提供的多个地址域内动态变化,增大攻击者地址搜索范围,增大攻击者流量监听难度。在此基础上,建立了IPv6主动防御模型。给出了双重随机地址生成算法,保证了地址的随机性,给出了快速切换和过保留两个地址切换策略,保证了地址切换过程中通信持续有效。从地址和流量两方面对模型的安全性进行了理论分析,从功能和性能两方面对模型进行了实验测试。理论分析与实验测试结果表明所提出的模型可有效提高攻击者开销,保护网络安全。     

无线网状网中基于干扰模型的多信道分配策略

为解决信道干扰导致无线网状网吞吐量下降的问题,本文提出一种新的基于干扰模型的多信道分配策略.首先对网络进行分层,然后按照优先级逐层进行信道分配,通过降低信道间的干扰来提高每个结点的吞吐量,进而提高整个网络的吞吐量.仿真结果表明了该策略的有效性.     

基于IPv6的无线自组网在物联网中的应用

通过对基于IPv6的无线自组网的介绍和研究,将传感网和承载网共同组网,可以更好的发挥各自的优势,同时弥补各自的不足。这种网络搭配具有很广泛的应用场景。     

异构无线网络中基于人工神经网络的自适应垂直切换算法

针对当前基于人工神经网络的垂直切换算法(ANN-VHO),存在业务自适应性差和计算复杂度高的问题,该文提出一种基于人工神经网络的自适应垂直切换算法。首先,根据终端获取到的接收信号强度(RSS),采用阈值判断的方法,遴选出候选网络集;其次,根据该文划分的不同业务类型,对参数进行自适应选择和归一化;再次,把选择的参数输入人工神经网络,判决出候选网络集中最佳的接入网络。最后,实验结果表明,该算法能根据用户的业务类型合理地选择切换网络,降低切换阻塞率,同时降低算法的时间复杂度。     

An Efficient Causal Structure Learning Algorithm Based on Recursive Simultaneous Equations Model

A new algorithm, the RSEM （Recursive simultaneous equations model） algorithm, is presented for causal structure learning under the LSEM （Linear structural equations model）. The algorithm effectively applies recursive simultaneous equations model to causal structure learning. This paper makes two specific contributions. Firstly, under the assumption that knowing the causal order of the variables, we show that recursive simultaneous equations model can be used for causal structure learning under the LSEM regardless of whether the datasets follow multivariate Gaussian distribution. Secondly, the performance of the RSEM algorithm is compared with the state-of-the-art algorithms on 7 networks. Simulation results show that the RSEM algorithm outperforms existing algorithms in terms of time performance, and has a quite high accuracy for thresholds 0.005 and 0.01.     

LLN中基于能量均衡的高效低时延路由算法

针对有损低功耗网络(Low-power and Lossy Network,LLN)中由于无线链路的有损特性以及节点部署不均匀无法有效实现网络能量均衡,提出一种基于能量均衡的高效低时延路由算法(Efficient Low Latency Routing Algorithm Based on Energy Balance in Low-Power and Lossy Networks,ELLEB-RPL)。该算法采用“ELLEB组网”策略,使得节点能够有效避免在DODAG(Destination Oriented Directed Acyclic Graph)间来回切换;通过采用“最优父节点选择”策略,使得节点选择的父节点达到最优;通过采用“流量自适应分配”策略,达到网络能量均衡的目的。仿真结果表明,ELLEB-RPL在Sink节点平均吞吐量、网络平均寿命以及端到端时延上均有提升。