上下文感知计算若干关键技术研究
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摘要
计算技术的发展需要与之相适应的计算模式。随着同时具有计算和组网能力设备的大量出现以及这些设备的小型、微型和嵌入化,传统以计算机为中心的计算模式因无法克服“一人多机”所带来的困扰而受到严重挑战。目前,由Mark Weiser提出的以“透明”和“随处可用”为主要特征的普适计算设想因契合了计算技术发展的需求正受到广泛关注。在普适计算中“透明”指的并非完全是物理上的不可见性,更主要的是指用户与计算机之间的交互是否为用户所觉察。正如人们能利用环境上下文避免显示交互一样,计算机也可利用所能感知到的上下文采用蕴涵式的方式进行交互。这种蕴涵的交互方式正是普适计算实现透明交互的重要途径,并也由此发展成为一个独立的研究领域——上下文感知计算。显然它的研究对普适计算设想的实现至关重要。
本文针对普适环境下上下文感知技术的应用需求,首先分析了上下文感知计算的研究现状,提出了上下文和上下文感知计算的定义以及狭义和广义上下文感知计算的划分原则,通过对现有上下文感知计算系统的分析和总结,建立了上下文感知计算的概念模型,并对上下文感知计算的建模、系统框架和应用等问题进行了重点讨论。从而为进一步的研究提供基础和指导。
由于现有的上下文感知计算建模方法存在复杂度高、代价大、难于仿真等问题,本文提出了一种规范化的可支持快速原型构建的建模方法。该建模方法以Ptolemy II为平台,在上下文规范化建模的基础上,结合层次化建模和有限状态机等方法,通过系统层次化、模型细化和状态精化等步骤对系统实施建模。实例研究表明,该建模方法能方便快速地构建上下文感知计算系统,并可为部分和完整地研究这类系统提供一个系统级的仿真环境。
上下文推理是上下文感知计算的关键问题之一。本文利用感知计算中上下文的层次化特点提出了一种用于上下文推理的快速贝叶斯网络自学习算法,通过对贝叶斯网络结构预先进行合理假设,从而缩小了目标搜索空间,降低了算法的时间复杂度,提高了算法的可用性。理论和实验分析均表明,该算法能在较少量数据支持下在较快的时间内查找到与理想结构吻合度较高的贝叶斯结构,是一种面向感知计算的实用贝叶斯网络自学习算法。
系统框架是上下文感知计算能否被快速开发和广泛部署的关键指标。本文以多Agent技术为基础,提出了一种新的上下文感知计算系统框架。该框架以环境Agent为中心,从而解构了感知器与应用之间的紧密耦合关系,利用感知和演化Agent进行上下文的感知和推理,借助管理Agent实现安全与隐私策略,与人和其它应用的交互则通过用户和应用Agent实现。
上下文感知除了可用于一般应用外,也可用于路由或系统优化等。针对MANET网络的应用需求,本文提出了一种移动感知的分区MANET路由协议,该协议可通过感知各移动节点的链路状态上下文来自适应地隔离移动异常的节点从而避免频繁的无效路由计算和请求,降低路由开销。
通过对上下文感知计算建模、演化、系统框架和应用等问题的研究,本文建立了上下文感知计算的全局视图,提出了若干适用于感知计算的关键技术和算法,这可为感知计算更广泛的研究和部署提供基础和有效指导。
The development of computation technology makes the computation paradigm adaptable to it. With the occurrence of equipments with computation and network ability, and the trend to become smaller and embedded, the traditional computation paradigm considering one computer as the core of a system no longer meet the needs, because it cannot overcome the difficulty coming from“one person, many computer”. Pervasive computation paradigm proposed by Mark Weiser which takes“transparent”and“everywhere availability”as the main characteristic has received widespread attention in recent years since it meets the demand of computation technology.“Transparent”in pervasive computing does not only refer to the physical invisibility, but also refers to the interaction invisibility between the human and the computer. Like the human can avoid obvious interaction using contexts, a computer also may use sensed contexts for interaction via some implicit methods. Obviously, this implicit interaction way is a very important way to realize“transparent”in pervasive computing and now it become a hot research topic– context-aware computing.
Aimming at the demand of context-aware applications under pervasive environment, this dissertation first gives a literature review on the state-of-the-art of context-aware computing; then we proposes the principle of division of context-aware computing in its narrow sense and broad sense; after that we make a discussion on the context-aware computing modeling, context-aware system infrastructure and its applications. After reviewing the existing context-aware systems, we propose a conceptual model of context-aware computing which can set up a solid base for future research in this field. Conceptually, the existing context-aware models have the drawbacks of high complexity, high cost and high modeling difficulty. To solve these problems, this dissertation proposes a standard modeling methodology which supports fast prototype development. Under the platform of Ptolemy II, based on standardized modeling of contexts, Combined the hierarchization modeling method and finite state machine(FSM) method, the methodology propose a standardized process which include steps like system hierarchization, sub-model refinement and state refinement to support context-aware systems modeling. The simulation results indicate that the modeling methodology can facilitate and speed up the development of context-aware systems, and can provide a system-level simulation environment for studying context-aware system partially or completely.
One of the key issues in context-aware computing is the context inference. Obviously, complete and precise inference is impractical. The bayesian network is an appropriate inference tool in context-aware system. However, searching the optimal bayesian network in many cases is a NP-complete problem. On the other hand, a sub-optimal Bayesian Network can be obtained if the toplogy of the network can be predefined with some prior knowledge on the applications. This dissertation proposes a fast algorithm with low computation complexity. Theoretical and experimental results all show that the algorithm can find a bayesian network similar with the optimal one with affordable search time. Therefore, we say that the algorithm is a practical algorithm for context-aware computing.
System infrastructure is a key factor in fast development and wide deployment of context-aware system. Based on multi-agent technology, this dissertation proposes a novel system infrastructure for context-aware system. The infrastructure takes environment agent as the center, thus decoupling the relations of sensors with applications. It uses the sensors and evolution agents to do context sense and evolution. The management agents are used to realize security and privacy strategy, while the user and application agent are used to interactive with user and other applications. In addtion, the context-aware can be used in routing algorithm and system optimization. This dissertation proposed a mobility-aware zoned MANET routing protocol, which can sense the link state context between mobile nodes and then isolate unusual node adaptively which can avoid invalid routing computing and requests and then reduce routing costs.
Our contribution lies in the following aspects: 1) through the study on context-aware computing modeling, context evolution, system infrastructure and context-aware applications, this dissertation establishes a global view of context-aware computing; 2) it proposes many key technologies and algorithms for context-aware computing. All of these can provide effective direction and guidelines on researching and deployment of context-aware system.
本文针对普适环境下上下文感知技术的应用需求,首先分析了上下文感知计算的研究现状,提出了上下文和上下文感知计算的定义以及狭义和广义上下文感知计算的划分原则,通过对现有上下文感知计算系统的分析和总结,建立了上下文感知计算的概念模型,并对上下文感知计算的建模、系统框架和应用等问题进行了重点讨论。从而为进一步的研究提供基础和指导。
由于现有的上下文感知计算建模方法存在复杂度高、代价大、难于仿真等问题,本文提出了一种规范化的可支持快速原型构建的建模方法。该建模方法以Ptolemy II为平台,在上下文规范化建模的基础上,结合层次化建模和有限状态机等方法,通过系统层次化、模型细化和状态精化等步骤对系统实施建模。实例研究表明,该建模方法能方便快速地构建上下文感知计算系统,并可为部分和完整地研究这类系统提供一个系统级的仿真环境。
上下文推理是上下文感知计算的关键问题之一。本文利用感知计算中上下文的层次化特点提出了一种用于上下文推理的快速贝叶斯网络自学习算法,通过对贝叶斯网络结构预先进行合理假设,从而缩小了目标搜索空间,降低了算法的时间复杂度,提高了算法的可用性。理论和实验分析均表明,该算法能在较少量数据支持下在较快的时间内查找到与理想结构吻合度较高的贝叶斯结构,是一种面向感知计算的实用贝叶斯网络自学习算法。
系统框架是上下文感知计算能否被快速开发和广泛部署的关键指标。本文以多Agent技术为基础,提出了一种新的上下文感知计算系统框架。该框架以环境Agent为中心,从而解构了感知器与应用之间的紧密耦合关系,利用感知和演化Agent进行上下文的感知和推理,借助管理Agent实现安全与隐私策略,与人和其它应用的交互则通过用户和应用Agent实现。
上下文感知除了可用于一般应用外,也可用于路由或系统优化等。针对MANET网络的应用需求,本文提出了一种移动感知的分区MANET路由协议,该协议可通过感知各移动节点的链路状态上下文来自适应地隔离移动异常的节点从而避免频繁的无效路由计算和请求,降低路由开销。
通过对上下文感知计算建模、演化、系统框架和应用等问题的研究,本文建立了上下文感知计算的全局视图,提出了若干适用于感知计算的关键技术和算法,这可为感知计算更广泛的研究和部署提供基础和有效指导。
The development of computation technology makes the computation paradigm adaptable to it. With the occurrence of equipments with computation and network ability, and the trend to become smaller and embedded, the traditional computation paradigm considering one computer as the core of a system no longer meet the needs, because it cannot overcome the difficulty coming from“one person, many computer”. Pervasive computation paradigm proposed by Mark Weiser which takes“transparent”and“everywhere availability”as the main characteristic has received widespread attention in recent years since it meets the demand of computation technology.“Transparent”in pervasive computing does not only refer to the physical invisibility, but also refers to the interaction invisibility between the human and the computer. Like the human can avoid obvious interaction using contexts, a computer also may use sensed contexts for interaction via some implicit methods. Obviously, this implicit interaction way is a very important way to realize“transparent”in pervasive computing and now it become a hot research topic– context-aware computing.
Aimming at the demand of context-aware applications under pervasive environment, this dissertation first gives a literature review on the state-of-the-art of context-aware computing; then we proposes the principle of division of context-aware computing in its narrow sense and broad sense; after that we make a discussion on the context-aware computing modeling, context-aware system infrastructure and its applications. After reviewing the existing context-aware systems, we propose a conceptual model of context-aware computing which can set up a solid base for future research in this field. Conceptually, the existing context-aware models have the drawbacks of high complexity, high cost and high modeling difficulty. To solve these problems, this dissertation proposes a standard modeling methodology which supports fast prototype development. Under the platform of Ptolemy II, based on standardized modeling of contexts, Combined the hierarchization modeling method and finite state machine(FSM) method, the methodology propose a standardized process which include steps like system hierarchization, sub-model refinement and state refinement to support context-aware systems modeling. The simulation results indicate that the modeling methodology can facilitate and speed up the development of context-aware systems, and can provide a system-level simulation environment for studying context-aware system partially or completely.
One of the key issues in context-aware computing is the context inference. Obviously, complete and precise inference is impractical. The bayesian network is an appropriate inference tool in context-aware system. However, searching the optimal bayesian network in many cases is a NP-complete problem. On the other hand, a sub-optimal Bayesian Network can be obtained if the toplogy of the network can be predefined with some prior knowledge on the applications. This dissertation proposes a fast algorithm with low computation complexity. Theoretical and experimental results all show that the algorithm can find a bayesian network similar with the optimal one with affordable search time. Therefore, we say that the algorithm is a practical algorithm for context-aware computing.
System infrastructure is a key factor in fast development and wide deployment of context-aware system. Based on multi-agent technology, this dissertation proposes a novel system infrastructure for context-aware system. The infrastructure takes environment agent as the center, thus decoupling the relations of sensors with applications. It uses the sensors and evolution agents to do context sense and evolution. The management agents are used to realize security and privacy strategy, while the user and application agent are used to interactive with user and other applications. In addtion, the context-aware can be used in routing algorithm and system optimization. This dissertation proposed a mobility-aware zoned MANET routing protocol, which can sense the link state context between mobile nodes and then isolate unusual node adaptively which can avoid invalid routing computing and requests and then reduce routing costs.
Our contribution lies in the following aspects: 1) through the study on context-aware computing modeling, context evolution, system infrastructure and context-aware applications, this dissertation establishes a global view of context-aware computing; 2) it proposes many key technologies and algorithms for context-aware computing. All of these can provide effective direction and guidelines on researching and deployment of context-aware system.
引文
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