Pervasive location acquisition technologies: Opportunities and challenges for geospatial studies

The rapid development and increasing availability of various location acquisition technologies provide geospatial studies with both opportunities and challenges. These opportunities and challenges are discussed in this paper focusing on the following three aspects: the massive acquisition of location data and data quality, the analysis of massive location data and pattern discovery, and privacy protection for massive location data. This paper examines the current status of and the potential opportunities for geospatial research in these three areas and notes the major challenges. Finally, the development of this special issue is described, and the four articles included in this special issue are presented.     

基于Tapestry系统的DDoS攻击及其预防策略

由于结构松散,节点可以动态地加入和退出,安全性问题已经成为P2P网络所面临的主要挑战之一。Tapestry系统中攻击者可以利用系统的软状态机制,污染资源定位指针列表,控制主控端,发起DDoS攻击。基于身份认证的策略可以保护资源定位指针列表不受攻击者的污染,从而预防了DDoS攻击的发生。     

Computational humanities: the new challenge for VR

The Virtual Reality Applications Center at Iowa State University has been applying VR to the arts and humanities for many years. Our multidisciplinary research began in the area of virtual heritage, reconstructing historical locations and creating compelling artistic environments such as Nexus. Our work is evolving toward environments that accurately represent a particular location and include the activities that took place into that location. As we move in that direction, we are facing exciting challenges that renew our enthusiasm in VR. This article reflects our experiences integrating VR into the area of computational humanities.     

Indoor location based services challenges,requirements and usability of current solutions

Indoor Location Based Services (LBS), such as indoor navigation and tracking, still have to deal with both technical and non-technical challenges. For this reason, they have not yet found a prominent position in people’s everyday lives. Reliability and availability of indoor positioning technologies, the availability of up-to-date indoor maps, and privacy concerns associated with location data are some of the biggest challenges to their development. If these challenges were solved, or at least minimized, there would be more penetration into the user market. This paper studies the requirements of LBS applications, through a survey conducted by the authors, identifies the current challenges of indoor LBS, and reviews the available solutions that address the most important challenge, that of providing seamless indoor/outdoor positioning. The paper also looks at the potential of emerging solutions and the technologies that may help to handle this challenge.     

无线传感器网络定位技术研究进展

在无线传感器网络（WSNs）中,通过对节点的定位以确定事件发生的位置是WSNs需要具备的基本功能。介绍了WSNs定位技术的国内外研究现状,分析了静态传感器网络定位、移动信标节点定位和移动传感器网络定位的原理及方法,讨论了几种主要算法的优缺点,给出了移动传感器网络定位技术进一步研究的方向与面临的挑战。     

移动分布式环境下服务适配系统研究

移动环境给分布式资源共享特别是服务发现和资源定位带来了新的挑战。本文分析了移动性给服务发现和资源定位机制带来的特殊性,介绍了具有服务主动适配能力的服务适配原型系统Service CatalogNet,给出了其中的关键技术：适应移动性需求的支持多样性的服务模型、服务主动适配策略以及基于模糊匹配的服务定位机制。     

位置隐私研究综述

近年来随着传感器和无线移动设备的飞速发展,随时随地获得个人位置成为可能。一方面,促进了基于位置服务的飞速发展,另一方面,个人位置隐私泄露的问题引起人们的广泛关注。由于移动环境中位置信息的特殊性,造成无法直接利用现有的关系数据库隐私保护技术。文章分析了位置隐私保护中存在的挑战问题,从系统结构、位置匿名技术和查询处理技术三方面归纳总结了现有的研究工作,并指出了未来的研究方向。     

物联网位置隐私保护综述

位置信息是物联网感知信息的基本要素之一,也是物联网提供基于位置服务的前提.位置信息在带来服务便利的同时,其泄露也带来诸多威胁.物联网位置隐私保护已成为当前的研究热点之一.综述了物联网位置隐私保护领域现有的工作,阐述了物联网位置隐私保护的目标与挑战,重点介绍物联网在定位过程、基于位置服务以及边信息中的位置隐私泄露方式及对应的位置隐私保护机制,并探讨了物联网位置隐私保护技术未来的发展方向.     

Location awareness in ad hoc wireless mobile networks

Networks composed of dynamically repositioning mobile hosts require location awareness to provide new geographic services and to maximize routing efficiency and quality of service. Because wireless networks can operate in a 3D physical environment, exploiting mobile hosts' location information is both natural and inevitable. Emerging geographic services based on mobile ad-hoc networks (manets) must confront several challenges, including how to increase positioning accuracy and how to establish a connection from location information to the vast body of Web data, as in a tour-guide system for example     

PERSONAF: framework for personalised ontological reasoning in pervasive computing

Pervasive computing creates possibilities for presenting highly personalised information about the people, places and things in a building. One of the challenges for such personalisation is the creation of the system that can support ontological reasoning for several key tasks: reasoning about location; personalisation of information about location at the right level of detail; and personalisation to match each person’s conceptions of the building based on their own use of it and their relationship to other people in the building. From pragmatic perspectives, it should be inexpensive to create the ontology for each new building. It is also critical that users should be able to understand and control pervasive applications. We created the PERSONAF (personalised pervasive scrutable ontological framework) to address these challenges. PERSONAF is a new abstract framework for pervasive ontological reasoning. We report its evaluation at three levels. First, we assessed the power of the ontology for reasoning about noisy and uncertain location information, showing that PERSONAF can improve location modelling. Notably, the best ontological reasoner varies across users. Second, we demonstrate the use of the PERSONAF framework in Adaptive Locator, an application built upon it, using our low cost mechanisms for non-generic layers of the ontology. Finally, we report a user study, which evaluated the PERSONAF approach as seen by users in the Adaptive Locator. We assessed both the personalisation performance and the understandability of explanations of the system reasoning. Together, these three evaluations show that the PERSONAF approach supports building of low cost ontologies, that can achieve flexible ontological reasoning about smart buildings and the people in them, and that this can be used to build applications which give personalised information that can provide understandable explanations of the reasoning underlying the personalisation.     

基于模式匹配度的用户移动规则挖掘及位置预测方法研究

传统的移动用户位置预测方法由于模式支持度计算方式不合理,存在预测精度偏低的问题。为此,提出了一种基于模式匹配度的用户移动规则挖掘及位置预测方法,并将其用于移动通信系统中,以基台覆盖范围网格为单元的用户位置预测。具体包括三个步骤：通过图的遍历挖掘用户移动模式、基于用户移动模式生成用户移动规则和依据用户移动规则进行位置预测。实验分析使用10个批次轨迹数据进行用户移动规则挖掘,结果表明,该方法挖掘出的用户移动规则数少、支持度高和置信度高,具有高精度的优点。     

Advances towards high‐resolution pack‐and‐go displays: A survey

Abstract— Tiled displays provide high resolution and large scale simultaneously. Projectors can project on any available surface. Thus, it is possible to create a large high‐resolution display by simply tiling multiple projectors on any available regular surface. The tremendous advancement in projection technology has made projectors portable and affordable. One can envision displays made of multiple such projectors that can be packed in one's car trunk, carried from one location to another, deployed at each location easily to create a seamless high‐resolution display, and, finally, dismantled in minutes to be taken to the next location — essentially a pack‐and‐go display. Several challenges must be overcome in order to realize such pack‐and‐go displays. These include allowing for imperfect uncalibrated devices, uneven non‐diffused display surfaces, and a layman user via complete automation in deployment that requires no user invention. We described the advances we have made in addressing these challenges for the most common case of planar display surfaces. First, we present a technique to allow imperfect projectors. Next, we present a technique to allow a photometrically uncalibrated camera. Finally, we present a novel distributed architecture that renders critical display capabilities such as self‐calibration, scalability, and reconfigurability without any user intervention. These advances are important milestones towards the development of easy‐to‐use multi‐projector displays that can be deployed anywhere and by anyone.     

大田监测中无线传感器网络的部署

监测是无线传感器网络最具潜力的应用之一,其中传感器结点的部署是无线传感器网络中重要的问题,因为它反映了传感器网络的成本和监视能力.尽管国外已经在这方面开展了一些相关研究,由于不同的应用有不同的部署特点和目标,仍然面临很多挑战.本文综合无线传感器网络部署最新研究结果,分析了无线传感器网络中结点部署问题的重要性、面临的主要挑战,以及下一步的研究方向,并以环境监测中部署算法的设计为例,指出设计环境监测中无线传感器网络部署算法的关键因素.     

Efficient group communications in location aware mobile ad-hoc networks

The highly dynamic and uncertain character of mobile ad-hoc networks poses significant challenges for group management. Node mobility often changes the multicast tree, and therefore, frequent updates from group members are required to refresh the multicast tree at the source node. This paper presents Courier, a group communications algorithm that uses the location and velocity of roaming nodes to provide bandwidth efficient multicast between a source and its destinations (i.e., group members) in location aware mobile environments. Toward that end, Courier offers (1) a bandwidth efficient method for location updates from group members, (2) a mobility prediction model for predicting the movement of mobile group members, and (3) an overlay multicast data distribution tree (OMDDT) construction algorithm that is guided by the mobility prediction model. Comparisons of Courier to related multicast algorithms indicate an increase in data transmission success and a decrease in overall bandwidth consumption.     

TAPCS: Traffic-aware pseudonym changing strategy for VANETs

Location privacy is one of the main challenges in Vehicular Ad-hoc Networks (VANETs), since weak protection may hinder the public acceptance of this technology. Frequently changing pseudonyms are commonly accepted as a solution to protect the location privacy in VANETs. However, a simple pseudonym change is not enough to provide the required protection. Although many pseudonym changing strategies have been proposed to enhance the location privacy protection provided by this approach, the development of an effective strategy is not yet achieved. In this paper, we propose a new pseudonym changing strategy called Traffic-Aware Pseudonym Changing Strategy (TAPCS). The aim of this strategy is to provide an effective location privacy protection against the different types of pseudonyms linking attacks that can be performed by a strong passive adversary model. TAPCS is a distributed pseudonym changing strategy and is one of the strategies that use the radio silence technique. Unlike the existing distributed pseudonym changing strategies that use this technique, TAPCS aims to provide a high level of location privacy protection without impacting the safety in the VANETs. The analytical evaluation and simulation results demonstrate the effectiveness of the proposed strategy.     

面向移动社会网络的用户年龄与性别特征识别

移动社会网络数据存在网络结构复杂,节点间标签相互影响,包含交互信息、位置信息等多种复杂信息等特点,给识别用户的特征带来了许多挑战。针对这些挑战,通过分析一个真实的移动网络数据,利用统计学分析提取出已标记的不同特征用户间的差异,并利用这些差异,借助关系马尔可夫网络建立预测模型对未标记用户的年龄与性别进行特征识别。分析表明,不同年龄、性别的用户在不同时段的通话概率、通话熵,位置信息的分布、离散性,在社会网络中的集聚程度,以及相互之间二元、三元的交互频率方面都存在明显的差异。利用这些特征,提出了利用二元和三元交互的关系基团模板,结合用户自身的时间空间特征,通过关系马尔可夫网络计算用户特征的全联合分布概率,进而以此推断用户的年龄与性别的方法。经过实验分析,利用关系马尔可夫网络、用户时空信息和用户交互的关系基团的分类方法相较于传统的C4.5决策树、随机森林、Logistic回归和Naive Bayes等分类方法,能够提高最高约8%的预测准确率。     

Generation of an adaptive simulation driven by product trajectories

The tracking of products trajectories involves major challenges in simulation generation and adaptation. Positioning techniques and technologies have become available and affordable to incorporate more deeply into workshop operations. We present our 2-year effort into developing a general framework in location and manufacturing applications. We demonstrate the features of the proposed applications using a case study, a synthetic flexible manufacturing environment, with product-driven policy, which enables the generation of a location data stream of product trajectories over the whole plant. These location data are mined and processed to reproduce the manufacturing system dynamics in an adaptive simulation scheme. This article proposes an original method for the generation of simulation models in discrete event systems. This method uses the product location data in the running system. The data stream of points (product ID, location, and time) is the starting point for the algorithm to generate a queuing network simulation model.     

SELM: Semi-supervised ELM with application in sparse calibrated location estimation

Indoor location estimation based on Wi-Fi has attracted more and more attention from both research and industry fields. It brings two significant challenges. One is requiring a vast amount of labeled calibration data. The other is real-time training and testing for location estimation task. Traditional machine learning methods cannot get high performance in both aspects. This paper proposed a novel semi-supervised learning method SELM (semi-supervised extreme learning machine) and applied it to sparse calibrated location estimation. There are two advantages of the proposed SELM. First, it employs graph Laplacian regularization to import large number of unlabeled samples which can dramatically reduce labeled calibration samples. Second, it inherits the good property of ELM on extreme training and testing speed. Comparative experiments show that with same number of labeled samples, our method outperforms original ELM and back propagation (BP) network, especially in the case that the calibration data is very sparse.     

Locating experience: touring a pervasive performance

Touring location-based experiences is challenging, as both content and underlying location services must be adapted to each new setting. A study of a touring performance called Rider Spoke as it visited three different cities reveals how professional artists developed a novel approach to these challenges in which users drove the co-evolution of content and the underlying location service as they explored each new city. We show how the artists iteratively developed filtering, survey, visualization, and simulation tools and processes to enable them to tune the experience to the local characteristics of each city. Our study reveals how by paying attention to both content and infrastructure issues in tandem, the artists were able to create a powerful user experience that has since toured to many different cities.     

P3 systems: putting the place back into social networks

The availability of technologies enables a new class of location-aware information systems that link people-to-people-to-geographical-places (P3 systems). P3 systems can strengthen the relationship between social networks and physical places. They can also help individuals leverage location information to make new social ties and coordinate interactions that reinforce existing ties. Using the P3 systems framework, we describe the design space for location-aware community systems and important socio-technical challenges and opportunities.