Betweenness estimation in OLSR-based multi-hop networks for distributed filtering

In traditional networks special efforts are put to secure the perimeter with firewalls: particular routers that analyze and filter the traffic to separate zones with different levels of trust. In wireless multi-hop networks the perimeter is a concept extremely hard to identify, thus, it is much more effective to enforce control on the nodes that will route more traffic. But traffic filtering and traffic analysis are costly activities for the limited resources of mesh nodes, so a trade-off must be reached limiting the number of nodes that enforce them. This work shows how, using the OLSR protocol, the centrality of groups of nodes with reference to traffic can be estimated with high accuracy independently of the network topology or size. We also show how this approach greatly limits the impact of an attack to the network using a number of firewalls that is only a fraction of the available nodes.     

一种基于资源分配策略的复杂网络中心性测度

针对标准中心性测度不适用于非联通网络这一问题,提出了基于资源分配策略的复杂网络中心性测度。节点的资源分配中心性测度定义为节点从其它节点接受的资源量,如果一个节点从其他节点接受的资源量越多,则该节点越重要。通过人工网络和现实网络实验表明,该度量不仅适用于联通网络,也适用于非联通网络,相较于标准测度,可以检测桥节点,而且具有良好的稳定性。     

基于RBFCM和ECM的分层取证分析

为实现入侵证据的自动分析,设计一种基于取证图的分层取证分析方法。采用基于规则的模糊感知图模型,从局部识别出网络实体的状态,通过特征向量中心度计算得到重要的种子结点,再从大量攻击场景的关联结点中抽取攻击组。基于DARPA2000的实验结果表明,该方法在攻击组抽取和场景抽取方面具有较高的覆盖率和准确率。     

基于节点层级与标签传播增益的重叠社区发现?

多标签传播算法具有接近线性的时间复杂度,但用于重叠社区发现时存在精度低、稳定性差的问题。文中基于重叠节点更可能出现在社区边缘的思想,提出基于节点层级与标签传播增益的重叠社区发现算法。该算法首先利用改进的基于节点中心度与社区分布约束的单标签传播方法发现非重叠社区,并在标签传播过程中利用局部信息同步计算节点中心度。然后根据节点中心度定义节点层级函数,标记节点在所属社区中的层级。最后基于节点间的标签传播增益,利用新的多标签更新规则,获得重叠社区结构。实验表明该算法能有效提高精度和稳定性。     

基于SDK数据的城镇体系网络特征研究 ——以浙江省宁海县为例

“流空间”视角下,对城市体系的研究 逐渐由属性数据测度的静态等级结构转向关系 型数据测度的动态城市网络。以浙江省宁海县 为例,利用SDK数据表征各乡镇间的实测人流 联系强度,通过社会网络分析法、改进的优势 流法和位序—规模法测度城镇体系网络特征, 且与现行县域总体规划的城镇体系规划进行对 比。结果表明：一、宁海县各乡镇联系整体呈现 西强东弱、北强南弱的不均衡特征;二、第一、 第二和第三优势流主要向跃龙街道和桃源街 道汇集,且可识别区域内联系紧密的乡镇组合; 三、宁海县的人群流动通廊与规划轴线走向、 对外交通系统布局基本一致,西店镇、茶院乡— 力洋镇组合、前童镇—岔路镇组合的发展基本 符合规划设想,长街镇与规划设想尚有一定的 差距。为优化宁海城镇体系,建议采取统筹区域交通、强化重点乡镇中心性、整合要素资源等措施。本研究对于其他区域城镇体系的识别和规 划工作具有借鉴意义。     

区域中心的建筑几何诠释 评析普雷斯顿·斯科特·科恩的南京大学仙林校区学生活动中心设计

普雷斯顿·斯科特·科恩设计的南京大学仙林校区学生活动中心,通过建筑几何对具有向心性和终极性特征的校区核心建筑进行了诠释:内含作用力因果关系的几何体系表达了一种介于随意性和象征性之间的向心控制性;基于该体系的形态拉伸演变和丰富了建筑的时空体验,并以时间过程性重新定义终极性。设计对当地建造技术与经济现状的充分结合使这种诠释更具本土性。     

Investigation of road network features and safety performance

The analysis of road network designs can provide useful information to transportation planners as they seek to improve the safety of road networks. The objectives of this study were to compare and define the effective road network indices and to analyze the relationship between road network structure and traffic safety at the level of the Traffic Analysis Zone (TAZ). One problem in comparing different road networks is establishing criteria that can be used to scale networks in terms of their structures. Based on data from Orange and Hillsborough Counties in Florida, road network structural properties within TAZs were scaled using 3 indices: Closeness Centrality, Betweenness Centrality, and Meshedness Coefficient. The Meshedness Coefficient performed best in capturing the structural features of the road network. Bayesian Conditional Autoregressive (CAR) models were developed to assess the safety of various network configurations as measured by total crashes, crashes on state roads, and crashes on local roads. The models’ results showed that crash frequencies on local roads were closely related to factors within the TAZs (e.g., zonal network structure, TAZ population), while crash frequencies on state roads were closely related to the road and traffic features of state roads. For the safety effects of different networks, the Grid type was associated with the highest frequency of crashes, followed by the Mixed type, the Loops & Lollipops type, and the Sparse type. This study shows that it is possible to develop a quantitative scale for structural properties of a road network, and to use that scale to calculate the relationships between network structural properties and safety.     

TC-BAC: A trust and centrality degree based access control model in wireless sensor networks

Access control is one of the major security concerns for wireless sensor networks. However, applying conventional access control models that rely on the central Certificate Authority and sophisticated cryptographic algorithms to wireless sensor networks poses new challenges as wireless sensor networks are highly distributed and resource-constrained. In this paper, a distributed and fine-grained access control model based on the trust and centrality degree is proposed (TC-BAC). Our design uses the combination of trust and risk to grant access control. To meet the security requirements of an access control system with the absence of Certificate Authority, a distributed trust mechanism is developed to allow access of a trusted node to a network. Then, centrality degree is used to assess the risk factor of a node and award the access, which can reduce the risk ratio of the access control scheme and provide a certain protection level. Finally, our design also takes multi-domain access control into account and solves this problem by utilizing a mapping mechanism and group access policies. We show with simulation that TC-BAC can achieve both the intended level of security and high efficiency suitable for wireless sensor networks.     

A methodology for the characterization of flow conductivity through the identification of communities in samples of fractured rocks

We present a methodology that characterizes through the topology of a network the capability of flow conductivity in fractures associated to a reservoir under study. This strategy considers the fracture image as a graph, and is focused on two key aspects. The first is to identify communities or sets of nodes that are more conductive, and the second one is to find nodes that form the largest paths and have therefore more possibility of serving as flow channels. The methodology is divided into two stages, the first stage obtains the cross points from fracture networks. The second stage deepens on the community identification. This second stage carries out the process of identifying conductive nodes by using centrality measures (betweenness, eccentricity and closeness) for evaluating each node in the network. Then an optimization modularity method is applied in order to form communities using two different types of weights between cross points or nodes. Finally, each community is associated with the average value of each measure. In this way the maximum values in betweenness and eccentricity are selected for identifying communities with the most important nodes in the network. The results obtained allow us to show regions in the fracture network that are more conductive according to the topology. In addition, this general methodology can be applied to other fracture characteristics.     

中国城市等级体系问题的初步研究

城市等级结构问题的研究由来已久，但研究中通常用人口规模作为研究的基本材料，因而得出的结论不大符合实情。本文在前人工作的基础上，对克里斯塔勒的中心度计算公式略作修正，先找出不同的专业职能等级序列，再在专业职能等级序列的基础上加权求和，得出各省会城市和计划单列市在全国范围内的综合中心度，进而分析中国城市体系的等级结构。