普适计算中位置感知服务的研究
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摘要
普适计算是信息空间与物理空间的融合,在这个融合的空间中人们可以随时随地和透明地获得数字化的服务;计算机本身将从人们的视线中消失,人们注意力的中心将回归到要完成的任务本身。位置是普适计算中非常重要的上下文信息,普适计算中设备的许多行为都与位置上下文相关联。智能家电自动感知用户所处的位置,并提供适当服务,例如自动打开用户附近的灯或将来电自动转接到离用户最近的固定电话等,所有这些应用都需要判断用户的位置,以及用户与设备之间的相对位置关系。因此,位置感知计算在普适计算研究中占据举足轻重的地位。本文对普适计算中的位置感知服务问题展开了研究。本文的主要研究内容与创新点如下:
分析了现有国内外的室内小范围高精度位置感知定位系统,及其定位算法和定位技术。提出了一种基于超宽带的位置感知定位系统,采用极大似然距离估计法来定位,推导了超宽带距离估计的克拉-美罗CRLB下界,采用MATLAB进行了距离估计仿真。仿真结果表明:基于超宽带的极大似然距离估计定位系统的定位精度可以达到厘米级,对于位置感知定位是一种简便、有效的方法。
分析了现有普适计算的位置模型,构建了一种新的基于本体的通用位置感知模型,将基于不同技术的定位感知系统集成到普适计算环境中。提出了位置感知模型本体LMO。LMO采用Web本体语言OWL描述了位置感知模型中涉及到的感知上下文的词汇,包括空间、时间、用户、安全策略。该模型通过统一的语义位置方式,实现位置感知上下文知识的共享和重用。
采用本体推理机实现了位置感知上下文知识及其属性之间的推理。采用FaCT++推理机实现了LMO类的一致性检验,以及LMO类之间的分类推理。采用语义Web规则语言SWRL定义了属性与属性之间的关系。采用Jess Rule Engine规则引擎,对OWL+SWRL语言编写的规则实现了属性间的深层次推理。
提出了基于使用控制UCON_(ABC)的上下文访问控制模型CACM。CACM不仅关心授权,而且引入了职责和条件。针对位置感知计算中三种典型的上下文访问控制应用,灵活扩展了三种组合子模型,包括使用前授权+使用前条件模型、主动权力+被动权力模式、和使用前授权+使用前职责模型,为位置感知上下文访问控制提供了一个崭新的解决思路。
提出了位置感知计算中动态的、语义的安全策略管理机制,该机制在现有策略模型中加入了上下文提供者、本体服务两大部分。上下文提供者获得位置感知计算环境中各个实体的上下文变化。根据上下文的变化,本体服务主动更新相关策略信息,策略服务通过策略执行代理实现对被管理对象的动态操作。该机制解决了位置感知环境中既要保障信息共享和协作,又要保障信息安全和个人隐私之间的矛盾。
Pervasive computing, integrating of computer, communication and digital media technology, makes it possible to merge the physical world we are living in and the virtual world in the information space. The basic idea of pervasive computing is to embed computer into the living environment or tool of human, so as to make the computer invisible from users' sight and the users can only focus on their task instead of the computer. Location is an essential part of contextual information, which has turned out to be useful in many applications, particularly in determining position, navigation, routing, tracking, logistics, and monitoring of pervasive computing devices. For example, turning on the light near the user automatically, or transferring the phone to the nearest user and so on. All of these applications should be able to determine the user's position and the relative position to other devices. Consequently location-aware computing is one of the key but challenging areas of pervasive computing. In this dissertation, we focus on location-aware service in pervasive computing. Our approaches and contributions are given below.
All of existing location-aware systems, positioning algorithms and positioning technologies are analyzed. The positioning system based on Ultra-wideband (UWB) is proposed. We deduce Cramer-Rao lower bound (CRLB) of UWB distance estimation, and estimate distances using maximum likelihood estimator (MLE). All results of our work are simulated by MATLAB. These results demonstrate that the positioning system based on UWB successfully reaches centimeter scale in precision, and MLE is a simple and effective method for location-aware positioning.
After analyzing the existing location models, we construct a novel location-aware model based on ontology, which can integrate heterogeneous location-aware positioning systems into pervasive computing environment. The Location-aware Model Ontology (LMO) is also proposed in this dissertation. By using the Web Ontology Language (OWL), LMO describes location-aware context vocabularies including space, time, user profiles, and policies for security and privacy. So the location-aware information can be defined exactly, expressed clearly, and organized effectively in a uniform semantic mode. Context knowledge can be shared and re-used in security.
The reasoning between the location-aware context knowledge and its properties is carried through using ontology reasoner. By using FaCT++ (Fast Classification of Terminologies) reasoner, the classification hierarchy for the LMO classes is calculated, and inconsistencies of the LMO classes are checked. The relationships among the properties are defined through the rules coded in OWL and SWRL (Semantic Web Rule Language). The deeper reasoning of properties' relationships is performed by Jess Rule Engine.
A context access control model (CACM) based on UCON_(ABC) (Usage CONtrol) is presented. CACM not only focuses on authorization, but also introduces obligations, and conditions. Three integrated sub-models are extended flexibly, including pre-authentication & pre-condition model, active-provision & passive-provision model, and pre-authentication & pre-obligation model. The security, usefulness and flexibility of CACM are demonstrated by three typical location-aware application scenarios.
A dynamic and semantic security policy management mechanism for location-aware computing is presented. The mechanism extends the existing policy model by importing context provider and ontology service. The context changes of various entities in location-aware computing environment can be obtained by context provider. According to the context changes, ontology service updates the information of policy service and event service automatically. Then policy service adjusts the action on the managed targets by policy enforcement agent dynamically. The mechanism solves the contradiction between information sharing and security privacy in the location-aware computing environment.
分析了现有国内外的室内小范围高精度位置感知定位系统,及其定位算法和定位技术。提出了一种基于超宽带的位置感知定位系统,采用极大似然距离估计法来定位,推导了超宽带距离估计的克拉-美罗CRLB下界,采用MATLAB进行了距离估计仿真。仿真结果表明:基于超宽带的极大似然距离估计定位系统的定位精度可以达到厘米级,对于位置感知定位是一种简便、有效的方法。
分析了现有普适计算的位置模型,构建了一种新的基于本体的通用位置感知模型,将基于不同技术的定位感知系统集成到普适计算环境中。提出了位置感知模型本体LMO。LMO采用Web本体语言OWL描述了位置感知模型中涉及到的感知上下文的词汇,包括空间、时间、用户、安全策略。该模型通过统一的语义位置方式,实现位置感知上下文知识的共享和重用。
采用本体推理机实现了位置感知上下文知识及其属性之间的推理。采用FaCT++推理机实现了LMO类的一致性检验,以及LMO类之间的分类推理。采用语义Web规则语言SWRL定义了属性与属性之间的关系。采用Jess Rule Engine规则引擎,对OWL+SWRL语言编写的规则实现了属性间的深层次推理。
提出了基于使用控制UCON_(ABC)的上下文访问控制模型CACM。CACM不仅关心授权,而且引入了职责和条件。针对位置感知计算中三种典型的上下文访问控制应用,灵活扩展了三种组合子模型,包括使用前授权+使用前条件模型、主动权力+被动权力模式、和使用前授权+使用前职责模型,为位置感知上下文访问控制提供了一个崭新的解决思路。
提出了位置感知计算中动态的、语义的安全策略管理机制,该机制在现有策略模型中加入了上下文提供者、本体服务两大部分。上下文提供者获得位置感知计算环境中各个实体的上下文变化。根据上下文的变化,本体服务主动更新相关策略信息,策略服务通过策略执行代理实现对被管理对象的动态操作。该机制解决了位置感知环境中既要保障信息共享和协作,又要保障信息安全和个人隐私之间的矛盾。
Pervasive computing, integrating of computer, communication and digital media technology, makes it possible to merge the physical world we are living in and the virtual world in the information space. The basic idea of pervasive computing is to embed computer into the living environment or tool of human, so as to make the computer invisible from users' sight and the users can only focus on their task instead of the computer. Location is an essential part of contextual information, which has turned out to be useful in many applications, particularly in determining position, navigation, routing, tracking, logistics, and monitoring of pervasive computing devices. For example, turning on the light near the user automatically, or transferring the phone to the nearest user and so on. All of these applications should be able to determine the user's position and the relative position to other devices. Consequently location-aware computing is one of the key but challenging areas of pervasive computing. In this dissertation, we focus on location-aware service in pervasive computing. Our approaches and contributions are given below.
All of existing location-aware systems, positioning algorithms and positioning technologies are analyzed. The positioning system based on Ultra-wideband (UWB) is proposed. We deduce Cramer-Rao lower bound (CRLB) of UWB distance estimation, and estimate distances using maximum likelihood estimator (MLE). All results of our work are simulated by MATLAB. These results demonstrate that the positioning system based on UWB successfully reaches centimeter scale in precision, and MLE is a simple and effective method for location-aware positioning.
After analyzing the existing location models, we construct a novel location-aware model based on ontology, which can integrate heterogeneous location-aware positioning systems into pervasive computing environment. The Location-aware Model Ontology (LMO) is also proposed in this dissertation. By using the Web Ontology Language (OWL), LMO describes location-aware context vocabularies including space, time, user profiles, and policies for security and privacy. So the location-aware information can be defined exactly, expressed clearly, and organized effectively in a uniform semantic mode. Context knowledge can be shared and re-used in security.
The reasoning between the location-aware context knowledge and its properties is carried through using ontology reasoner. By using FaCT++ (Fast Classification of Terminologies) reasoner, the classification hierarchy for the LMO classes is calculated, and inconsistencies of the LMO classes are checked. The relationships among the properties are defined through the rules coded in OWL and SWRL (Semantic Web Rule Language). The deeper reasoning of properties' relationships is performed by Jess Rule Engine.
A context access control model (CACM) based on UCON_(ABC) (Usage CONtrol) is presented. CACM not only focuses on authorization, but also introduces obligations, and conditions. Three integrated sub-models are extended flexibly, including pre-authentication & pre-condition model, active-provision & passive-provision model, and pre-authentication & pre-obligation model. The security, usefulness and flexibility of CACM are demonstrated by three typical location-aware application scenarios.
A dynamic and semantic security policy management mechanism for location-aware computing is presented. The mechanism extends the existing policy model by importing context provider and ontology service. The context changes of various entities in location-aware computing environment can be obtained by context provider. According to the context changes, ontology service updates the information of policy service and event service automatically. Then policy service adjusts the action on the managed targets by policy enforcement agent dynamically. The mechanism solves the contradiction between information sharing and security privacy in the location-aware computing environment.
引文
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