一种基于用户行为预测的群移动性管理模型

移动性管理是未来5G移动的重要组成部分,如何均衡寻呼负载和位置更新开销,从而合理利用无线资源是当前的研究重点.提出了一种新的群移动性管理(GMM)方案,可以针对具有相同运动特征的用户进行集中式管理,从而可以减少单个用户移动性管理(SMM)时存在的重复开销.仿真结果表明,GMM比SMM可以获得更佳的运行开销.     

SDN assisted self organizing network architecture for multi-RAT networks and mobility prediction

Wireless Networks - Existing and future wireless networks are expected to have multiple Radio Access Technologies (RAT), primarily due to legacy reasons and introduction of newer technologies....     

一种基于ELM预测的NDN移动性支持方法

命名数据网络（NDN）架构是信息中心网络思想指导下的新一代网络架构,移动性支持方法是命名数据网络架构下的主要研究点。传统的生产者端移动性支持方法都采取事后应对的方式,对消费者而言,该方法无法保证切换过程的透明性。针对上述问题,提出了一种基于ELM预测的移动性支持方法PB,该方法对原有前向转发表进行修改,并增加了新的控制消息分组使得网络中相应节点可以针对预测算法的结果进行提前调整,并且兴趣分组多播的方式使得无论何时发生切换,生产者终端都能立即对兴趣分组进行响应,同时方法针对预测可能失败的问题提供了快速恢复网络原有状态的方法。仿真实验表明,本文提出的PB移动性支持方法相比于RP和IP移动性支持方法能显著降低切换时延,减少因切换导致的分组丢失。     

A cluster based mobility prediction scheme for ad hoc networks

The ad hoc networks are completely autonomous wireless networks where all the users are mobile. These networks do not work on any infrastructure and the mobiles communicate either directly or via other nodes of the network by establishing routes. These routes are prone to frequent ruptures because of nodes mobility. If the future movement of the mobile can be predicted in a precise way, the resources reservation can be made before be asked, which enables the network to provide a better QoS. In this aim, we propose a virtual dynamic topology, which on one hand, will organize the network as well as possible and decreases the impact of mobility, and on the other hand, is oriented user mobility prediction. Our prediction scheme uses the evidence theory of Dempster–Shafer in order to predict the future position of the mobile by basing itself on relevant criteria. These ones are related to mobility and network operation optimisation. The proposed scheme is flexible and can be extended to a general framework. To show the relevance of our scheme, we combine it with a routing protocol. Then, we implemented the prediction-oriented topology and the prediction scheme which performs on it. We implemented also a mobility prediction based routing protocol. Simulations are made according to a set of elaborate scenarios.     

A multi-dimensional crime spatial pattern analysis and prediction model based on classification

This article presents a multi-dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification-based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime-prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real-world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases.     

An architecture of knowledge management system based on agent and ontology

To solve the problems in knowledge management system （KMS）, such as information sharing, the ability to extend and re-engineer, and the reusable ability of legacy systems in distributed and heterogeneous environments. This article presents a method based on agent and ontology of designing KMS. This method consists of two agencies. One is knowledge agency with three agents supporting knowledge management process. The other is application agency with three agents supporting knowledge application. In this method, ontology is used to represent the knowledge in knowledge base and the content in the message exchanged among agents. To demonstrate the advantages of this method, experiments have been carried out and the results imply that this method is efficient and effective for small and medium-size enterprises to design KMS.     

Crime hotspot prediction based on dynamic spatial analysis

Crime is not a completely random event but rather shows a pattern in space and time. Capturing the dynamic nature of crime patterns is a challenging task. Crime prediction models that rely only on neighborhood influence and demographic features might not be able to capture the dynamics of crime patterns, as demographic data collection does not occur frequently and is static. This work proposes a novel approach for crime count and hotspot prediction to capture the dynamic nature of crime patterns using taxi data along with historical crime and demographic data. The proposed approach predicts crime events in spatial units and classifies each of them into a hotspot category based on the number of crime events. Four models are proposed, which consider different covariates to select a set of independent variables. The experimental results show that the proposed combined subset model (CSM), in which static and dynamic aspects of crime are combined by employing the taxi dataset, is more accurate than the other models presented in this study.     

QoS provisioning in cellular networks based on mobility prediction techniques

In cellular networks, QoS degradation or forced termination may occur when there are insufficient resources to accommodate handoff requests. One solution is to predict the trajectory of mobile terminals so as to perform resource reservations in advance. With the vision that future mobile devices are likely to be equipped with reasonably accurate positioning capability, we investigate how this new feature may be used for mobility predictions. We propose a mobility prediction technique that incorporates road topology information, and describe its use for dynamic resource reservation. Simulation results are presented to demonstrate the improvement in reservation efficiency compared with several other schemes.     

Fast square root architecture based on prediction of result bits

A new architecture for the fast evaluation of the square-root of normalized binary numbers is presented. It exploits the fact that depending upon the relative magnitudes of the partial result and the partial remainder at any stage of a non-restoring square-root algorithm, a large number of result bits can be predicted. This allows one to convert approximately two thirds of the additions in the square-root procedure to shifts at the cost of a marginal increase in the hardware.     

Attack path prediction method based on causal knowledge net

The existing attack path prediction methods can not accurately reflect the variation of the following attack path caused by the capability of the attacker.Accordingly an attack path prediction method based on causal knowledge net was presented.The proposed method detected the current attack actions by mapping the alarm sets to the causal knowledge net.By analyzing the attack actions,the capability grade of the attacker was inferred,according to which adjust the probability knowledge distribution dynamically.With the improved Dijkstra algorithm,the most possible attack path was computed.The experiments results indicate that the proposed method is suitable for a real network confrontation environment.Besides,the method can enhance the accuracy of attack path prediction.     

基于云计算和大数据的知识服务平台架构研究

随着海量信息和数据的几何式增长,传统数据库复杂的检索和使用方式造成有效情报不容易清晰筛选与精准定位;对信息和数据的片面析出不能充分把握技术竞争情报和产学研上下游结构;如何解决这个困惑和难题,是一个值得研究的课题。文章以云计算和大数据为基础,进行知识服务平台的架构研究。     

基于移动预测模型的ad hoc网络稳定链路度量

提出了一种基于移动预测模型的稳定链路度量算法，定义了稳定邻居度量和本地运动度量2种测度。根据这2种测度，移动预测模型利用LZ78算法对本地节点与其邻居的稳定性概率进行预测，从而找到其最稳定邻居，为选择稳定路由提供依据。仿真结果表明此算法明显优于直方图算法及最小ID算法，所选链路的稳定性能显著提高。     

基于上下文的机场目标识别方法

提出了一种基于上下文的机场目标识别方法,将机场各组成部分间存在的依赖关系应用于识别技术中,以提高识别效率。根据机场目标具有明显的方向性这一特点,使用Gabor滤波器对输入图像进行滤波,将图像信息按不同尺度和方向分解至多个通道,获取相应的特征图,并利用Radon变换从特征图中提取线特征。通过分析组成机场目标的各线特征之间的相互关系,利用上下文信息,制定一系列判决准则,实现对机场目标的有效识别。     

基于频域和空域分析的帧内预测模式快速选择算法

基于DCT变换的能量聚集和方向特性,首先利用AC系数对块尺寸进行预先选择,然后利用AC系数的方向性对16×16块进行模式预先选择,接着利用空域相关性对4×4块进行快速模式选择,有效缩小了模式选择的范围。实验表明,与现有同类算法相比,在质量几乎相当的情况下,本算法速度明显提高。     

A signaling and control architecture for mobility support in wireless ATM networks

This paper presents a signaling and control architecture for mobility support in a wireless ATM network that provides integrated broadband services to mobile terminals. A system level protocol architecture for a wireless ATM network is outlined. The proposed protocol stack incorporates new wireless link MAC, DLC and wireless control sublayers, together with appropriate mobility extensions to the existing ATM network control layer. Wireless control and ATM signaling capabilities required for mobility support are discussed, and preliminary solutions are given for selected major functions. Potential extensions to standard Q.2931 ATM signaling are proposed to support handoff and service parameter/QoS renegotiation required for mobility. An associated wireless control protocol for supporting terminal migration, resource allocation, and handoff is discussed. Preliminary experimental results are given which validate the proposed handoff control protocol on an ATM network testbed.     

基于CORBA的分布式系统向Web服务架构迁移技术

CORBA是一种已经成熟的分布式计算模型，很多分布式系统均构建在此结构之上，但，其紧密耦合特性限制了其在Internet上的进一步发展，Web服务成为一种分布式计算的新的实现方法．现阐述了Web服务的基本技术规范，介绍了一种基于SOAP的CORBA架构向Web服务架构迁移技术。     

A contention-free mobility management scheme based on probabilisticpaging

In forthcoming personal communication systems (PCSs), small cells are deployed to achieve high spectral efficiency. This has significant impacts on location tracking of mobile users. The increase in location update (LU) load leads to more contention on the reverse control channel. Thus, many algorithms are designed to distribute the LU load to a larger number of cells. This avoids the inefficiency of random accessing due to high offered load. In an alternative approach (Wong 1995), a contention-free LU algorithm is proposed. Two or more mobile units are permitted to register with a base station simultaneously without contention. A probabilistic paging mechanism called Bloom filtering is used to select cells to be paged. Since there is no contention in LU, inefficiencies due to random accessing are bypassed. In this paper, we present another contention-free LU algorithm. It is hybrid in the sense that LUs are temporally or geographically triggered. The use of hybrid LU alleviates inefficiencies inherent to temporal triggered LU in Wong. Three selective paging schemes are considered in this paper. Tradeoff between paging delay and paging bandwidth is addressed. The performance of this algorithm is compared to Wong and other conventional strategies. Numerical results show that the new algorithm compares favorably with previous proposed strategies     

A network-assisted flow mobility architecture for optimized mobile medical multimedia transmission

A large part of mobile Health (mHealth) use-cases such as remote patient monitoring/diagnosis, teleconsultation, and guided surgical intervention requires advanced and reliable mobile communication solutions to provide efficient multimedia transmission with strict medical level Quality of Service (QoS) and Quality of Experience (QoE) provision. The increasing deployment of overlapping wireless access networks enables the possibility to offer the required network resources for ubiquitous and pervasive mHealth services. To address the challenges and support the above use-cases in today’s heterogeneous network (HetNet) environments, we propose a network-assisted flow-based mobility management architecture for optimized real-time mobile medical multimedia communication. The proposed system is empirically evaluated in a Pan-European HetNet testbed with multi-access Android-based mobile devices. We observed that the proposed scheme significantly improves the objective QoE of simultaneous real-time high-resolution electrocardiography and high-definition ultrasound transmissions while also enhances traffic load balancing capabilities of wireless architectures.     

一种基于Hadoop架构的并行挖掘算法研究

基于Hadoop架构,提出一种并行的决策树挖掘算法实现大数据集间的知识挖掘。通过MapReduce并行编程模式实现Hadoop架构下SPRINT并行挖掘算法的频繁项集,解决了大数据集挖掘效率低下,时间消耗量大的问题。SPRINT算法通过对原始数据集进行划分,并将分块数据发给不同Map进程并行计算,使系统存储和计算资源得到有效利用,运用MapReduce各计算节点将挖掘结果数据汇聚,减少中间结果数据量,使并行挖掘时间显著减少。SPRINT算法并行化实验表明,Hadoop架构下的SPRINT并行挖掘算法具有良好的可扩展性和集群加速比。